BackgroundSocial media provides timely proxy signals of mental health, but reliable tweet-level classification of depression subtypes remains challenging due to short, noisy text, overlapping symptomatology, and labeling bias. Large language models (LLMs) are increasingly used in mental health for tasks such as symptom extraction, risk screening, and triage, yet their reliability for fine-grained depression subtype […]
Extraction and processing of intensive care chart data from a patient data management system
BackgroundRoutine clinical data captured in Patient Data Management Systems (PDMS) in intensive care and perioperative settings are an invaluable resource for clinical research. However, the proprietary, fragmented, and transaction-oriented architecture of many systems severely limits secondary data use and requires extensive Extract, Transform, and Load (ETL) processing.MethodsWe developed a modular, Python-based ETL framework that enables […]
From bedside to bytes: the digital transformation of the healthcare workforce
Digital transformation is reshaping healthcare work, whereas research on workforce implications remains fragmented across disciplines. Effects like burnout, resistance, and workflow disruption are often framed as implementation failures rather than systematic outcomes of how work is reorganized. This Mini Review advances a four-dimensional analytical lens distinguishing work execution (task distribution, sequencing, temporal organization), work experience […]
An in-home engagement and usability study of GeRI: an open-source platform for remote symptom assessment and wearable activity monitoring in men with prostate cancer
Geriatric assessment (GA) is underused in oncology because clinic-based implementation is time- and resource-intensive, limiting routine evaluation of frailty and treatment tolerance. Existing digital tools often rely on proprietary devices and closed analytic pipelines. We developed the Geriatric Remote Initiative (GeRI), an open-source platform integrating a wrist-worn accelerometer, smart scale, and tablet interface with reproducible […]
Technology-driven diabetes care: innovation without equity?
Post Content
Thematic landscapes and temporal trends of disability technology adoption: insights from Structural Topic Modelling
IntroductionIn recent years, the importance of accessible and inclusive technologies has increasingly supported people with disabilities. However, prior studies on the adoption of technology remain fragmented, often focusing on specific disabilities or tools without exploring broader connections. Addressing this, the current study addresses the gaps by identifying core topics, examining temporal variations, and analyzing interrelations […]
“Reimaging a triage system with midwives, for midwives”: exploring preferences for a midwife-Led triage system in South Africa through a user-centered approach
IntroductionTriage in the maternity unit is critical to ensuring the delivery of timely and appropriate care. It is regarded as an initiative to reduce maternal mortality by accelerating the provision of appropriate care at the appropriate time. However, maternity units in South Africa lack standardized triage systems. Most pregnant women often wait for hours and […]
Validating an AI-assisted comentoring model for identifying at-risk students and for academic mentoring: a study protocol
BackgroundAcademic mentoring plays a critical role in monitoring student progress, maintaining academic integrity, identifying early signs of risk, and delivering personalized guidance to improve learning outcomes. Traditionally, this has relied on face-to-face interactions; however, advancements in artificial intelligence (AI) have introduced new opportunities for AI-assisted mentoring. While promising, many existing AI models for student monitoring […]
Editorial: Privacy enhancing technology: a top 10 emerging technology to revolutionize healthcare
Post Content
Performance of federated versus centralized learning for mammography classification across film–digital domain shift
IntroductionLarge, diverse datasets are essential for reliable deep learning in mammography, yet clinical data remain siloed due to privacy and governance constraints. Federated learning enables collaborative training without sharing raw data, but its robustness under strong imaging-domain heterogeneity, such as film–digital shifts, remains uncertain.MethodsWe conducted a comparative evaluation of centralized learning and cross-silo federated learning […]
Explainable and reproducible AI: culturally responsive AI for health equity in minoritized groups
Artificial intelligence (AI) is transforming healthcare by enabling advanced diagnostics, personalized treatments, and improved operational efficiencies. By identifying complex data patterns and correlations, AI could supplement clinical decision-making, enabling more rapid diagnoses and treatment decisions tailored to meet the unique needs of diverse communities. However, realizing these benefits requires that clinical AI models be consistent, […]
Negotiating privacy and responsibility in digital public health: a qualitative study of the social and ethical implications of peer-to-peer health data sharing
IntroductionPeer-to-peer sharing of personal health data on social media is increasingly used as a strategy to support public health goals. Such sharing is often assumed to motivate individuals to adopt or maintain healthy behaviors. However, the social and ethical implications of sharing-based interventions remain insufficiently examined. This paper offers an empirical and theoretical contribution by […]