Latest AI and machine learning research in information technology for healthcare professionals.
INTRODUCTION: The paradigm of personalized medicine is rapidly shifting from traditional, evidence-based genomics to advanced, data-driven ecosystems. Understanding this transition, supported by the computational tools of precision medicine, is critical for managing high-dimensional biomedical data. AREAS COVERED: Synthesizing current biomedical and medical informatics literature, this narrative r...
The widespread adoption of electronic health records (EHRs), which capture patient-specific longitudinal information on diagnoses, laboratory tests, clinical procedures, and outcomes, has created unprecedented opportunities to study diseases at scale. Integrating EHR data with genomic information offers novel ways to understand disease heterogeneity, identify biomarkers and therapeutic targets, an...
Eye-tracking-while-reading corpora are a valuable resource for many different disciplines and use cases. Use cases range from studying the cognitive p...
OBJECTIVES: There is limited data demonstrating the benefit of artificial intelligence technology in the diagnosis and triage of pulmonary embolism. O...
BACKGROUND: Point-of-care ultrasound (POCUS) is integral to obstetrics and gynecology (OBGYN), offering bedside diagnostic and therapeutic advantages....
BACKGROUND: Artificial intelligence (AI) has been increasingly recognized as a public health tool with applications ranging from epidemiology, pandemi...
Clinical decision-making in psychiatry has traditionally relied on rating scales and clinical impressions documented in the electronic health record (...
BACKGROUND: Chronic kidney disease (CKD) is a critical, progressive condition associated with high mortality and substantial healthcare costs. Early d...
Chemical, biological, radiological, and nuclear (CBRN) incidents present escalating risks across the Middle East and North Africa (MENA) amid geopolit...
STUDY OBJECTIVES: Sleep research has been limited by the lack of large, diverse polysomnography (PSG) datasets. Existing resources are often single-ce...
BACKGROUND: Artificial intelligence (AI) is increasingly applied to blood-demand forecasting, donor management, inventory optimisation, wastage reduct...
Advanced Clinical Decision Support Systems significantly influence patient care, with medicine prescriptions being a vital area of research. Ontology,...
BACKGROUND: Telemedicine is conventionally modeled as a dyadic clinician-patient encounter, yet a third party-caregiver, community health worker, nurs...
Prakriti, the Ayurvedic concept of individual somatic constitution, forms the foundation for personalized preventive and therapeutic strategies by cla...
Diabetes affects an estimated 828 million people worldwide; prevalence is growing rapidly in low- and middle-income countries (LMICs), with major heal...
Cancer incidence and mortality are rising globally, with their burden falling disproportionately on low-income and middle-income countries. Africa fac...
OBJECTIVE: Artificial intelligence (AI) shows promise for improving cancer management, but clinical adoption is limited by the absence of standardized...
BACKGROUND: AI has become increasingly used in mental health care for applications such as diagnosis, monitoring, and treatment support. These include...
BACKGROUND: Indoor navigation remains a major challenge for people with visual impairments, affecting autonomy, safety, and quality of life. While nav...
Synthetic data offer significant potential for cardiology research by enabling data sharing, preserving privacy, and supporting machine learning model...