niloofar mohammadzadeh

Mobile-based applications have become increasingly critical for healthcare delivery worldwide over the past few years. Developing a mobile application for hemophilia self-care is one of the tools that can provide helpful information about the disease, reminders, and treatment recommendations. This study aims to determine a minimum data set as the first step in developing a hemophilia self-care mobile application.

This descriptive-analytical study was conducted in 2023 and consisted of three steps. In the first step, relevant databases such as PubMed, Scopus, and Science Direct were reviewed. The data elements collected in the previous step were combined, and their validity was checked and confirmed in the second step. In the last step, all ten hematologists-oncologists at Imam Khomeini hospital complex, affiliated with Tehran university of medical sciences, completed a questionnaire to score the identified elements. Statistical analysis was performed using SPSS (Ver 16).

Based on global guidelines, published research, and specialists' feedback, the minimum data set for hemophilia management was developed. There are four main categories and twenty-three subclasses of identified elements, including demographic data (5 elements), disease management-related data (12 elements), educational data (3 elements), and technical capabilities (3 elements). To determine the importance of each data element, we calculated the percentage points provided by specialists, which were 95.50% for demographic data, 96.45% for disease management-related data, 95.83% for educational data, and 95.83% for technical capabilities.

Due to the lack of hemophilia’s minimum data set at the national level, this study can serve as a turning point toward standardized data collection for this disease. By utilizing these precise, coherent, and standard data elements, hemophilia management and quality of life can be improved.

Rheumatoid arthritis is a systemic, chronic autoimmune disease that affects the joints, and limited mobility. The disease is progressive and can significantly impact a patient's quality of life. Today, mobile applications have the potential to address specific health needs and provide therapeutic interventions. The initial stage of constructing and advancing a healthcare information system involves the utilization of a minimum data set, which comprises essential and standardized data components aimed at capturing and overseeing patient care. This study aims to identify key components for a mobile-based self-care application for patients with rheumatoid arthritis.

In this descriptive analytical study, two steps were undertaken. Firstly, a review of related articles and existing apps was conducted. Secondly, a researcher-developed questionnaire with a high reliability coefficient (Cronbach's alpha=0.97) was used to validate the identified information elements. Elements that scored at least an average of 3.2 (60%) on a 5 point Likert scale were deemed necessary data components for the design of an android-based mobile app catering to the self-care needs of rheumatoid arthritis patients.

Based on the analysis findings, experts identified crucial technical requirements for a mobile-based self-management system. The system should include features for documenting drug side effects and providing educational content and physical exercise videos. Additionally, these requirements encompass reminders for medication, doctor appointments, and physical activities. Priorities also include clinical information, lifestyle management, and patient demographics.

Overall, the implementation of such a system has the potential to enhance patients' self-management skills, promote active involvement in self-care, and facilitate communication with healthcare providers.

This study was conducted to classify the types of evaluation methods in clinical health technolo-gies based on a systematic review method.

An electronic search was conducted in three scientific databases including Scopus, PubMed and ISI. The search strategy was performed in Jul to Nov 2021 and based on the three main concepts of "evaluation", "technology", "health. This search has been restricted to 10 years (2011-2021). Moreover, it only was limited to English and papers published in journals and conferences proceeding.

Overall, 8149 references were identified for title and abstract screening. Full text screening was per-formed for 2674 articles, with 174 meeting the criteria for study inclusion.

Most of the technologies evaluated in these articles were associated with PC-based systems (N=107), and there have been fewer mobile apps (N=67). Most of used technologies were with goals of treat-ment (43%, N=74) and education (26%, N=45). Among all the methods, the most and the least used methods were usability (66%, N=115) and qualitative (1%, N=2) method, respectively. The most method for health clini-cal technologies is usability method especially in telemedicine field.

According to the report of the World Health Organization, overweight and chronic and psychological diseases caused by it have reached an alarming level in the world. Today, cognitive behavioral therapy as a specific method for controlling overweight teaches the audience how to identify and change inappropriate behavior patterns and destructive thoughts with distress that negatively affect their behavior and emotions. The purpose of this research was to provide a mobile-based application for overweight control with a cognitive-behavioral therapy approach.

This research was of applied-developmental type. In the first stage, by examining the available applications based on mobile and related to weight control and also Beck cognitive therapy protocol for weight loss, the capabilities of the application were identified and then based on a survey of experts, these capabilities were determined. Afterwards, the user interface of the application was designed and the necessary coding was done to use it. The database was then created using MySQL software and the application program was created using Flutter software and Dart programming language and was named CBTdiet. Finally, the usability of the application was evaluated by users using a standard QUIS questionnaire.

Based on the entry and exit criteria, among the 247 identified applications, the capabilities of 17 applications were examined. Finally, according to the opinion of the experts, 21 capabilities, including the ability to send motivational messages to the audience and the ability to reward to achieve weight loss of one kilogram per week, were considered for the design of the application program. The application designed in this research was at a good level from the users’ point of view with an average of 7.99±1.1 and was able to obtain an acceptable level of satisfaction in the evaluation stage. The software’s overall capabilities section got the highest average score (8.12) and the screen section got the lowest average score (7.89) among all sections.

Based on the determined capabilities, a mobile-based application for controlling overweight was designed and created with a cognitive behavioral therapy approach, and it can be effective in overweight control by modifying lifestyle and changing destructive thoughts.

Identifying risk factors is recommended as the first step for depression management in children and adolescents. This study aims to determine the data elements required for developing a clinical decision support system for screening major depression in young people.

This research was a descriptive-analytical study. The research population included a variety of mental health specialists that were both psychologists and students in psychiatry and guidance & counseling majors as well as electronic databases including Scopus, Pubmed, Embase, PsychInfo, WOS and Clinical key. The data collection tool was a questionnaire designed in three main sections which was answered by a convenient sample of 8 people who were specialists in the field. To analyze the extracted data Content Validity Ratio (CVR) and Mean measures were calculated for each item in questionnaire. Content Validity Index (CVI) and Cronbach’s Alpha (using SPSS software) were calculated which were equal to 0.74 and 0.824 respectively which confirmed validity and reliability of the research tool. 

 According to Lawshe’s table, data elements with CVR between 0 and 0.75 and Mean less than 1.5, like “Ethnicity and race” (CVR=-0.25, Mean=1.125), were rejected. Items such as “Gender” (CVR=0.5) with a CVR equal to or less than 0.75, as well as items with a CVR between 0 and 0.75 and a Mean equal to or more than 1.5, like “Marital status” (CVR=0.5, Mean=1.625) were retained and considered to be included as the minimum data set for screening major depression in ages 10 to 25 years. Data elements were categorized in three categories: Demographic, Clinical and Psychosocial

Clinical decision support systems can facilitate providing healthcare at different levels such as screening major depression. These systems can be used for screening major depression risk factors to improve accessibility to mental health practitioners, assure the implementation of guidelines and provide a common language between different levels of healthcare. Determining the minimum data set for screening major depression in ages 10 to 25 years, is the first step toward developing a clinical decision support system for screening individuals for major depression.

Providing early health care services in natural disaster is one of the essential applications of telemedicine. This narrative review aims to investigate the applications, advantages and challenges of telemedicine in natural disaster-stricken areas. Medline (through PubMed), Web of Science (WOS), and Scopus databases were searched for related articles published from beginning to 2022. The keywords used for the search included "telemedicine" and "natural disaster." After removing duplicate papers, irrelevant review articles and letters to editors, 44 relevant papers were selected and reviewed. Information sharing through audio, visual, and data-oriented services is among critical approaches that telemedicine services mainly use. Teleconsultation, tele-education, remote interpretation, tele-psychiatry, and tele-surgery are among measures that can be implemented in emergencies like earthquakes, fires, floods, storms, and drought. The fundamental requirements of a telemedicine-oriented system for providing emergency services in natural disasters include wireless scales, conversation tools, blood pressure monitor, respiratory rate monitor, spo2 sensor, glucometer, portable ultrasound unit, wearable thermometers, virtual stethoscopes, portable three leads electrocardiograph monitor, and digital otoscopes. Simple telemedicine systems can have many advantages in the natural disasters. However, the main challenge in this regard is to adapt the necessary communication systems to a telemedicine paradigm. Another critical challenge is to interpret and apply the summary of acquired information and the inevitable interaction outcomes at the required time and place.

Social networks that provide users with health data not only educate them but also play an active role in the health decision-making process. Health social networks, in addition to being a good tool for better patient communication with health care providers, can play an effective role in connecting similar patients with each other to receive social support. Social networking is one of the biggest achievements of Web 2, which facilitates communication between people. Despite the spread of social networks, their use in the field of health is still at its early levels. To implement an information system, it is first necessary to identify, design and model the related processes. The main purpose of this study was to provide technical documentation for the development of social networks in the field of health in order to facilitate future developments.

This study was an applied research. Due to the review of texts in the first phase, this research was descriptive. It is also a developmental research due to its technological dimensions in modeling and pattern model presentation. First, extracted features were confirmed based on experts’ opinions. Then, according to the identified features, social network modeling was performed at three levels of data, functional and process. Based on the modeling, a prototype model was designed and evaluated.

In this research, technical documents were prepared for the development of social networks in the field of health in the three axes of data modeling, functional modeling and process modeling. In the usability assessment by Nielsen model, the created prototype based on modeling was evaluated. Finally, the number of problems in each case of the Nielsen model was determined. The case of "Visibility of system status" with 26.31 and "Consistency and standards" with 5.27 were associated with the highest and lowest problems, respectively.

The growing need and expansion of the use of social networks has created a good platform for using this tool in the field of health and exploiting its benefits. The present study focuses on providing technical documentation for the development of health social networks and to facilitate the development of social networks in the field of health.

Meaningful use program indicates that health care organizations make meaningful use of an accredited electronic health record system. The objective of this study was to investigate the process of “meaningful use” program and the related challenges for the development of electronic health record.

This review study was conducted in 2020. The PubMed, Scopus, Science Direct, and Google scholar databases were searched from 2010 to October 2019 using “Meaningful Use Program” and “Electronic Health Record” as keywords. After applying the inclusion criteria, 20 articles were reviewed.

Based on the studies, the measures related to “Meaningful Use” program included 15 main measures, 5 selected sub-measures, and 6 qualitative clinical measures. The program includes three steps: data recording and sharing, advanced clinical processes, and improving health outcomes. The primary criteria for receiving the incentive amount of “Meaningful Use” program included computerized physician order entry, investigation of drug interactions, creation of electronic prescriptions, and registration of demographic characteristics. The challenges of this program included the time-consuming nature of the program, the lack of control over infrastructure development, unusable technologies of electronic health records, and the all-or-nothing approach to certification.

The use of new programs and solutions like “Meaningful Use” program can lead to the development of electronic health record and enables more secure exchange of information.

Sepsis is the most important disease in the first 28 days of life and one of the main causes of infant mortality in the intensive care unit. Its definitive diagnosis is possible by performing blood culture. Neonatal sepsis can be a clinical sign of nosocomial infections that are often resistant to antibiotics. Therefore, the purpose of this study was to create and evaluate a hospital sepsis prediction model and present its results to health care providers.

In this descriptive-applied study, the research population includes neonates admitted to the intensive care unit of Valiasr Hospital in Tehran and the research sample is the data of 4196 neonates admitted to this ward from 2016 to August, 2020. The initial features for creating a predictive model of sepsis were prepared by examining the relevant information sources and under the supervision of professors and officials of Valiasr Hospitalchr('39')s mother and fetus research center and its validity was confirmed by 5 neonatal professors of this hospital. In this research, machine learning algorithms have been used to create a sepsis prediction model.

Accuracy and AUROC(area under the ROC curve) parameters were used to evaluate the generated models. The highest values of Accuracy and AUROC are related to Adaptive Boosting and random forest algorithms, respectively.

Learning curves show that using different training examples and more complex selection of combination features improves the performance of the models. Further research is needed to evaluate the clinical effectiveness of machine learning models in a trial.

Epilepsy is a neurological disorder characterized by seizures and recurrent attacks. Self-management leads to seizure control and maximizes the quality of life in epileptic patients. The purpose of this study was to evaluate the quality of applications available in the epileptic google play store based on the rating features of MARS (Mobile Applications Rating Scale).

The search was conducted systematically using the keywords "epilepsy", "seizure", "mobile health" at the Android google play store. Data were extracted and analyzed from Feb 2018 to Apr 2019.

Accordingly, 45 apps were identified potentially relevant of which 20 met inclusion criteria. Twenty-five apps were excluded because they were unrelated to epilepsy self-management, or not Development for people with epilepsy, not in English language or were not free and available. The total mean MARS score was 3.21 out of 5, and more than half of apps (17, 85%) had a minimum acceptability score of 3.0. The mean of apps’ items were 3.27 in Engagement, 3.96 in function, 3.30 in Aesthetics, 2.96 in Information and 2.73 in subjective quality items.

Few apps meet prespecified criteria for quality, content, and functionality for epilepsy self-management. Despite the rapid evolution of self-management apps, lack of validation studies is a significant concern that limits the clinical value of these apps. Moreover, having a guideline and benchmarking in the field of mobile application development, in epilepsy management, can help analyze the content of established applications.

Oral soft tissue diseases include a broad spectrum, and the wide array of patient data elements need to be processed in their diagnosis. One of the biggest and most basic challenges is the analysis of this huge amount of complex patient data in an increasing number of complicated clinical decisions. This study seeks to identify the necessary steps for collecting and management of these data elements through establishing a consensus‑based framework.

This research was conducted as a descriptive, cross‑sectional study from April 2016 to January 2017, which has been performed in several steps: literature review, developing the initial draft (v. 0), submitting the draft to experts, validating by an expert panel, applying expert opinions and creating version v.i, performing Delphi rounds, and creating the final framework.

The administrative data category with 17 and the historical data category with 23 data elements were utilized in recording data elements in the diagnosis of all of the different oral diseases. In the paraclinical indicator and clinical indicator categories, the necessary data elements were considered with respect to the 6 main axes of oral soft tissue diseases, according to Burket’s Oral Medicine: ulcerative, vesicular, and bullous lesions; red and white lesions of the oral mucosa; pigmented lesions of the oral mucosa; benign lesions of the oral cavity and the jaws; oral and oropharyngeal cancer; and salivary gland diseases.

The study achieved a consensus‑based framework for the essential data element in the differential diagnosis of oral medicine using a comprehensive search with rich keywords in databases and reference texts, providing an environment for discussion and exchange of ideas among experts and the careful use of the Delphi decision technique.

To design, develop, and evaluate a clinical decision support system (CDSS) to decrease the adverse effects of treatment in Childhood Leukemia. To achieve high accuracy, a knowledge base CDSS was designed based on the viewpoints provided by experts and clinical references. The system has the capability of medical report documentation, drug prescription, dosage determination, and displaying patients’ medical history. It is also able to eliminate the problems caused by prescription and drug dosage errors by considering the patient’s status. By documenting the patients’ medical report, the system can provide comprehensive information and precise recommendations about the future readmission and drug dosage accuracy. The system achieved 94.5% sensitivity, 93% accuracy, and 80% specificity in the evaluation phase. Application of such systems in the process of prescribing drugs can improve the quality of patient care by reducing the probability of pharmaceutical errors.

Pelvic floor disorders are a common disease which, with varying degrees of severity, disrupts daily life and also decreases the quality of life of the individual. This disease can be cured by lifestyle modifications and self-care education; on the other hand, smartphones have become a good platform for health services and therapeutic interventions. The aim of this study was to identify information and educational components for the self-care application of women with pelvic floor disorders.

This descriptive study was performed in Yas Hospital affiliated to Tehran University of Medical Sciences. According to Morgan table, 30 gynecologists who were randomly selected were included in the study. The data gathering tool was a researcher-made questionnaire which its validity and reliability were confirmed (α=0.85) and its content was provided by reviewing the scientific sources.

The results of the analyzes showed that from the experts’ point of view the interventional section including reminders, daily activities diaries and targeting with an average score of 4.14 has been of great importance. Since then, the applied and self-care section with an average score of 4.364is ranked second in priority.

According to a survey by experts who play a major role in the management of the disease. The essential components of this application were identified in three main sections consist of: electronic records, the interventional section and the practical and self-care and their subsections.

Many diseases require constant monitoring todays, and online communication with patients for timely intervention is necessary. In this study, based on the results of these studies, we investigated the factors affecting telemedicine admission in Parkinson's patients.

This research was a descriptive survey. The tool of this research is a researcher-made questionnaire that was based on library and internet studies in valid databases such as Medline, Science direct (Elsevier), and searching for original research articles between 2000 and 2017. To search for keywords in the design of a telemedicine software, Parkinson's disease, Technology Acceptance Model in English-language databases.
The questions were designed with the Likert spectrum. The validity of the questionnaire was assessed by the opinions of five experts. Content validity index was measured and item with CVI score higher than 0.79 was considered appropriate. Reliability was assessed through Cronbach's alpha. Statistical sample was determined using sample size determination method in two cities of Tehran and Shiraz. In this study, structural equation modeling (SEM) was used. SPSS software version 16 was used for data analysis. The final data analysis was done by modeling in Smart PLS version 3 software

For each t-statistic, the path between the two variables was examined, and the statistics whose magnitude was greater than 1.96, at a confidence level of 95%, considering the same path that represents the strength and power of the effect between the two variables, the research hypotheses were statistically and in sample. Examined. Of the 19 hypotheses considered for the adoption of the research technology model, 16 were accepted.

Ease of use is one of the most influential factors on attitudes in Parkinson's patients in Iran. Technology anxiety is one of the most important factor that reduce the acceptance of portable smart systems. The Parkinson's patient user does not recognize recreation as a useful system, but the inclusion of educational content to promote health in the program will make Parkinson's patients more welcomed. If the software is prescribed by the therapist, its acceptance rate in Parkinson's patients will increase.

Nowadays, the role of smart systems and developed tools such as wearable systems for monitoring the patients and controlling their conditions consistently has increased significantly. The present research sought to identify the factors which are essential for designing a wearable smart blanket system and modeling the proposed systems.

To this aim, the requirements for creating the proposed system in ambulance were described after determining the features related to wearable systems by conducting on a comparative study. First, some studies were performed to identify the wearable system development. Then, the elicited questionnaire was given to the physicians and medical informatics specialists. Finally, the extracted requirements were implemented for modeling a smart blanket system.

Based on the results, the wearable smart blanket system includes some specific characteristics such as monitoring the important signs, communicating with the surroundings, processing the signals instantly, and storing all important signs. In addition, they should involve some nonfunctional characteristics such as easy installment and function, interactivity, error fault tolerance, low energy consumption, and the accuracy of sign stability. Then, based on the requirements and data elements extracted from the questionnaire, the system was modeled as a detailed design of the proposed technical blanket system. Based on the results, the architecture of the designed system could provide expected scenarios by using the Active Review for Intermediate Design‑oriented scenario‑based evaluation method.

Today, smart systems and tools have considerably developed in terms of monitoring the patients and controlling their conditions. Therefore, wearable systems can be implemented for monitoring the health status of patients in ambulance.

In recent years, women’s demand to enter sport stadiums has turned to one of the most controversial topics. The discussion continuity has led to numerous opinions by scientific and religious scholars. The aim of the presented paper is to investigate and criticize their documents for and against the presence of women in stadiums. Studies show, obstacles and challenges persist despite ratifications of laws and legal protections for women. Therefore, it is essential for women to make benefit of the protection mechanism of Islamic human rights because of their history, extension, and unique privileges. In addition, public awareness improvement, revision on the dynamic jurisprudence of Shiite and religious Ijtihad, developing legal - implemental solutions, and new laws ratification are required in order to safeguard and guarantee women’s needs and rights.

Nowadays, smart systems and advanced tools such as wearable systems have grown significantly in order to monitor patients and keep their condition under control. The aim of this study was to determine the requirements for designing a wearable smart blanket system (WSBS) to monitor patients in ambulance instantaneously.

After reviewing the characteristics of wearable systems by conducting a comparative study, the requirements for designing the proposed system were determined using appropriate data collection methods. In the first step, studies were conducted to identify the requirements for the development of wearable systems, and in the second step, a questionnaire obtained from the studies was distributed among specialists, and based on the results obtained from the questionnaire, the requirements for designing the system were determined.

Wearable Smart Blanket System (WSBS) has special functional features such as monitoring of vital signs, ability to communicate with the environment, instantaneous processing of vital signs, the ability to alert when vital signs exceed the threshold, and the ability to record all the patients' vital signs. The main non-functional features of WSBS include easy installation and operation, interoperability, error tolerance, low power consumption, accuracy of signs recording, data evaluation and analysis.

The WSBS records all the vital signs needed for the control of patients seamlessly and provides interpreted data for the ambulatory treatment team. All patients' medical, diagnostic, and monitored health information are stored in the physician assistants' system, and therefore, allows them to provide early diagnosis.

Success of infection treatment depends on the availability of accurate, reliable, and comprehensive data, information, and knowledge at the point of therapeutic decision-making. The identification of a national minimum data set will support the development and implementation of an effective surveillance system. The goal of this study was to develop a national antimicrobial resistance surveillance minimum data set. In this cross-sectional and descriptive study, data were collected from selected pioneering countries and organizations which have national or international antimicrobial resistance surveillance systems. A minimum data set checklist was extracted and validated. The ultimate data elements of the minimum data set were determined by applying the Delphi technique. Through the Delphi technique, we obtained 80 data elements in 8 axes. The resistance data categories comprised basic, clinical, electronic reporting, infection control, microbiology, pharmacy, World Health Organization-derived, and expert-recommended data. Relevance coding was extracted based on the Iranian electronic health record coding system. This study provides a set of data elements and a schematic framework for the implementation of an antimicrobial resistance surveillance system. A uniform minimum data set was created based on key informants’ opinions to cover essential needs in the early implementation of a global antimicrobial resistance surveillance system in Iran.

Due to the widespread use of mobile-based systems, and the low cost of this technology, application of mobile-based self-management system can lead to adherence to the treatment and promotion of the health for the people living with human immunodeficiency virus (HIV). The purpose of this study was to identify requirements for the mobile-based self-management system for these people.

This study was a descriptive one, carried out in two main phases in year 2017. In the first stage, in order to identify the requirements for the mobile-based self-management system, similar articles were searched and reviewed, and in the second phase, identified requirements were validated using a researcher-made questionnaire. The statistical population was infectious diseases specialists affiliated with Tehran University of Medical Sciences, Iran. The collected data were analyzed using descriptive statistics methods.

The requirements for the self-management system were identified in four categories: demographic data requirements, clinical data requirements, technical capabilities, and self-management strategies. Furthermore, according to the research community' attitude, six data elements for demographic category, 10 data elements for clinical category, 11 features for technical capabilities, and 10 items for self-management strategies were selected.

Use of proposed requirements strategies can improve the self-management skills and medication adherence of the people living with human immunodeficiency virus, and facilitate their communication with health care providers.

Aim: Knee arthroplasty is one of the best treatments to reduce pain and improve quality of life in cases of osteoarthritis resistant to osteoarthritis, however since it is an offensive act and delayed arthroplasty may lead to unwanted side effects after surgery. Therefore, the correct and timely selection of the patient for knee arthroplasty is important so it is necessary to collect standard and integrated data necessary. The purpose of this research is to identify minimum data requirements for predicting knee arthroplasty in patients with osteoarthritis.
This is a descriptive study conducted in 2017. Effective factors in knee arthroplasty prediction were identified Through library research and Internet search of keywords such as total knee arthroplasty, minimal data set, ... in valid databases such as PubMed, science direct, ... and the Google search engine Scholar. Sampling was done using Morgan table 32 faculty members of where rheumatology specialist at Tehran University of Medical Sciences were selected as sample. Validity of the questionnaire was assessed by Health Information Management Professors and its reliability was 82% Cronbach's alpha in SPSS 16 software. Results were analyzed using Excel software.
The results of the two-stage Delphi technique include: nonclinical data (age, body mass index) and clinical data (rest pain, activity pain, quality of life, the x-ray findings, knee instability, knee deformity, and limited mobility). These are the Minimum data necessary for predicting the need of knee arthroplasty in osteoarthritis patients.
The results of this study can be considered as the first step in the development of intelligent knee arthroplasty prediction systems. Using these systems will be very useful in managing the waiting list of surgery in health centers.

Oral squamous cell carcinoma (OSCC) is a rapidly progressive disease and despite the progress in the treatment of cancer, remains a life-threatening illness with a poor prognosis. Diagnostic techniques of the oral cavity are not painful, non-invasive, simple and inexpensive methods. Clinical decision support systems (CDSSs) are the most important diagnostic technologies used to help health professionals to analyze patients’ data and make decisions. This paper, by studying CDSS applications in the process of providing care for the cancer patients, has looked into the CDSS potentials in OSCC diagnosis.
We retrieved relevant articles indexed in MEDLINE/PubMed database using high-quality keywords. First the title and then the abstract of the related articles were reviewed in the step of screening. Only research articles which had designed clinical decision support system in different stages of providing care for the cancer patient were retained in this study according to the input criteria.
Various studies have been conducted about the important roles of CDSS in health processes related to different types of cancer. According to the aim of studies, we categorized them into several groups including treatment, diagnosis, risk assessment, screening, and survival estimation.
Successful experiences in the field of CDSS applications in different types of cancer have indicated that machine learning methods have a high potential to manage the data and diagnostic improvement in OSCC intelligently and accurately.

Access to the same information in documents, makes possible the presentation of comparative statistic in the field of health. Minimum data set gives us a tool for collecting standards while using such standards facilitate communication between people and organizations involved in health care. This study aimed to determining minimum data in measuring novice students' health in Iran. This research was a descriptive-comparative study. A checklist was developed using a comparative study about data set of novice students in three leading countries in children health, the US, England, and Australia, as well as Iran. The checklist comprised minimum data set in novice students' health measurement. It was submitted to 49 medical professionals, sociologists, physicians, health information technology professionals, and family and school care experts using Delphi method. Sixty out of sixty-two elements that were at the poll with more than 75% agreement were considered as main elements; and two elements with 50-75% agreement were considered as proposed elements. Two elements with more than 80% agreement were added to measurement record: food and drug allergy, as well as physical activity. Information elements for assessing health measurement were introduced in three categories: demographic and societal information, medical examinations, and assessment of physicians. This can be considered a suitable collection for electronic and paper format documentation.

Nowadays there is no absolute treatment for gestational diabetes. Therefore, lifestyle management and selfcare are highly recommended. In this regard¡ the use of information technology such as mobile phones can help in the process of self-care to pregnant mothers. The purpose of the present research was designing and development of gestational diabetes self-care system based on mobile phones.
This applied-developmental study was done based on 4 phases. These phases included: determining the required data through the related literature review and questionnaires, designing processes scenarios and drawing the UML graphs through Rational Rose software, creating a prototype system using the Java programming language in Android studio software environment, and system usability evaluation via questionnaire.
In the first phase, 4 data elements were eliminated and 39 (with at least 55% response frequency) were considered necessary. In the fourth stage, with acquiring a minimum average score of 6.1, evaluators were satisfied with the usability of all aspects of the system.
The findings concerning determination of the required data based on the mobile phone system, designing, creating and consequently evaluating it in all usability axes indicated a good level of system usability. Accordingly¡ it is suggested that future studies be performed on clinical trials effectiveness of using this gestational diabetes self-care software or similar systems designed to control the diet of these patients.

Agents can provide suitable infrastructure for follow-up data analysis and Chronic Heart Failure (CHF) management due to their many advantages such as autonomy and pro-activeness. The aim of this article is to explain the key points which should appropriately be considered in designing a CHF management system.
In this literature review, articles with the following keywords were searched in ScienceDirect, Google Scholar and PubMed databases without regard to their publication year: multi-agent system, chronic heart failure, and chronic disease management.
In designing CHF management through a multi-agent system approach, there are key points in general and specific aspects that must be considered; for example, confidentiality and privacy, architecture, appropriate information and communication technology infrastructure, and legal and ethical issues.
Clearly, identifying and resolving technical and non-technical challenges are vital to the successful implementation of this technology. Thus, in the design and implementation of agent-based systems, many issues should be considered; for instance, reduced face-to-face communication between patients and doctors that can lead to increased stress in some CHF patients, appropriate architecture and application of communication standards and protocols, the mode of communication between agents, users’ attitudes, supporting stakeholders to use agent technology, sufficient budget, coverage of healthcare costs based on agent technology, financial capability, and identification of opportunities and barriers.

To demonstrate an architecture to automate the prehospital emergency process to categorize the specialized care according to the situation at the right time for reducing the patient mortality and morbidity.
Prehospital emergency process were analyzed using existing prehospital management systems, frameworks and the extracted process were modeled using sequence diagram in Rational Rose software. System main agents were identified and modeled via component diagram, considering the main system actors and by logically dividing business functionalities, finally the conceptual architecture for prehospital emergency management was proposed. The proposed architecture was simulated using Anylogic simulation software. Anylogic Agent Model, State Chart and Process Model were used to model the system.
Multi agent systems (MAS) had a great success in distributed, complex and dynamic problem solving environments, and utilizing autonomous agents provides intelligent decision making capabilities. The proposed architecture presents prehospital management operations. The main identified agents are: EMS Center, Ambulance, Traffic Station, Healthcare Provider, Patient, Consultation Center, National Medical Record System and quality of service monitoring agent.
In a critical condition like prehospital emergency we are coping with sophisticated processes like ambulance navigation health care provider and service assignment, consultation, recalling patients past medical history through a centralized EHR system and monitoring healthcare quality in a real-time manner. The main advantage of our work has been the multi agent system utilization. Our Future work will include proposed architecture implementation and evaluation of its impact on patient quality care improvement.