A5007830308- Mobile Health and mHealth Applications
- Medical Coding and Health Information
- Healthcare Policy and Management
- Electronic Health Records Systems
- Artificial Intelligence in Healthcare
- COVID-19 diagnosis using AI
- AI in cancer detection
- Emergency and Acute Care Studies
- Simulation-Based Education in Healthcare
- Psychosocial Factors Impacting Youth
- Telemedicine and Telehealth Implementation
- Digital Mental Health Interventions
- Surgical Simulation and Training
- Healthcare Operations and Scheduling Optimization
- Hospital Admissions and Outcomes
- Smoking Behavior and Cessation
- Healthcare Systems and Reforms
- Pressure Ulcer Prevention and Management
- Enhanced Recovery After Surgery
- Technology Use by Older Adults
- Nursing Diagnosis and Documentation
- Education, Safety, and Science Studies
- Virtual Reality Applications and Impacts
- Stroke Rehabilitation and Recovery
- Machine Learning in Healthcare
Hormozgan University of Medical Sciences
2013-2023
Indiana University
2022
Tehran University of Medical Sciences
2018-2020
Shiraz University of Medical Sciences
2013
Despite the growing use of mobile health (mHealth), certain barriers seem to be hindering mHealth applications in healthcare. This article presents a systematic review literature on associated with reported by healthcare professionals.This was carried out identify studies published from January 2015 December 2019 searching four electronic databases (PubMed/MEDLINE, Web Science, Embase, and Google Scholar). Studies were included if they perceived adoption providers' perspectives. Content...
Cancer is the second leading cause of death after cardiovascular diseases in world. Health professionals are seeking ways for suitable treatment and quality care these groups patients. Survival prediction important both physicians patients order to choose best way management. Artificial Neural Network (ANN) one most efficient data mining methods. This technique able evaluate relationship between different variables spontaneously without any prevalent data. In our study ANN Logistic...
Abstract Background The rapid prevalence of coronavirus disease 2019 (COVID‐19) has caused a pandemic worldwide and affected the lives millions. potential fatality led to global public health concerns. Apart from clinical practice, artificial intelligence (AI) provided new model for early diagnosis prediction based on machine learning (ML) algorithms. In this study, we aimed make prognosis COVID‐19 patients using data mining techniques. Methods set was obtained intelligent management system...
One of the effective indicators for determining efficiency and optimal use hospital resources is length stay (LOS). This study aimed to determine patients' factors affecting LOS in Children's hospital.A cross-sectional was performed on Children Hospital medical record database including 350 records (April 2015 Dec 2015). Records were selected by stratified random sampling with proportional allocation. Then predetermined demographic variables extracted through records. All statistical...
Patients with colorectal cancer who undergo surgery face many postoperative problems. These problems include the risk of relapse, side effects, and long-term complications.This study sought to design develop a remote monitoring system as technological solution for postdischarge care these patients.This research was conducted in 3 main steps: feature extraction, design, evaluation. After extraction from systematic review, necessary features were defined by 18 clinical experts Iran. In next...
Background: Hospitals need a system for evaluating and monitoring performance promotion the efficiency effectiveness of their services outcomes. Pabon Lasso model is graphical chart that can be used to identify current status level hospitals by combining hospital indicators, simultaneously. Therefore, this study aimed evaluate Hormozgan University Medical Sciences (HUMS) during six-year period using model. Methods: This descriptive includes all teaching non-teaching affiliated with HUMS....
Abstract Background: Understanding each of the factors affecting length hospitalization especially in surgery wards can play a major role planning for optimal use hospital resources. This study aims to determine stay (LOS) surgical ward and then provide technology-based solutions .Methods: In this cross-sectional study, 310 records were selected by systematic random sampling from hospitalized patients general teaching Bandar Abbas, situated sought Iran. order association 26 variables...
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