Pleural effusion cytology is critical for diagnosing benign and malignant conditions, yet manual interpretation remains time-consuming and prone to subjectivity. The increasing burden of malignant pleural effusion in resource-constrained settings highlights the need for automated diagnostic solutions. This study presents an ensemble deep learning framework combining ResNet50V2, DenseNet121, and InceptionV3 architectures with transfer learning for […]
ChatGPT in healthcare: perceptions, ethical considerations, and practice implications among healthcare professionals in Ecuador and other countries in the Americas: a cross-sectional survey study
BackgroundGenerative artificial intelligence tools, such as ChatGPT, are increasingly discussed in healthcare; however, evidence from Latin American professional settings is limited and must be interpreted in light of regional digital inequities and ethical concerns.ObjectiveTo examine awareness, ethical perceptions, usage patterns, and attitude determinants related to ChatGPT among HCPs practicing mainly in Ecuador and other countries […]
Medical visual question answering with multimodal: a systematic mini review (2023–2026)
Medical visual question answering (Med-VQA) has emerged as a critical application of artificial intelligence within a short period of time. Large language models (LLMs) and vision-language models (VLMs) have fundamentally rewritten the architecture of medical question answering (QA). This study aims to systematically analyze recent developments in Med-VQA. Like past methods, which were simple, text-heavy […]
Within-person modeling of postprandial glucose using multimodal wearable data
The widespread adoption of continuous glucose monitoring (CGM) and wearable sensing technologies has enabled large-scale collection of high-resolution physiological and behavioral data in real-world settings. However, the analytical frameworks needed to translate these data into actionable, individualized insights remain limited. In particular, many existing approaches rely on population-level analysis or controlled experimental designs, which often […]
Monitoring and evaluation of an artificial intelligence-enhanced wound care intervention in a rural health network: defining stakeholder expectations and shared priorities
IntroductionChronic, hard-to-heal, wounds such as diabetes-related foot ulcers, venous leg ulcers, and pressure injuries, represent a growing global burden, contributing to high morbidity, and increased healthcare costs and demands on clinical capacity. These challenges are amplified in rural and remote settings, where limited resources and availability of services, workforce shortages, and geographical barriers restrict access […]
A multidimensional ensemble pipeline for early detection of IUGR condition through CTG
Introduction: Intrauterine growth restriction (IUGR) is a major cause of perinatal morbidity and mortality, often associated with placental insufficiency and progressive alterations in fetal autonomic regulation. Cardiotocography (CTG) represents one of the most widely used tools for fetal monitoring, yet its interpretation remains challenging due to high inter-observer variability and the subtle nature of early […]
Non-contact REM/NREM sleep staging from piezoelectric signals using respiratory and body-movement features with auxiliary TWED-based respiratory stability measures
IntroductionNon-contact sleep monitoring based on under-mattress piezoelectric sensing is attractive for low-burden home use, but REM/NREM discrimination remains challenging. This study aimed to investigate whether respiratory pattern stability, quantified by Time Warp Edit Distance (TWED)-based respiratory interval sequence (RIS) similarity features, could improve discrimination between the two major sleep states within sleep itself.MethodsOvernight piezoelectric and […]
Beyond classification metrics: a psychometric-aware benchmark for data augmentation in imbalanced student mental health surveys
BackgroundMachine-learning-based depression screening from student survey data complements clinician assessment but faces two obstacles: class imbalance (causing under-prediction of urgent minority cases) and the untested assumption that synthetic augmentation data preserve psychometric validity. Although recent work has begun to evaluate distributional fidelity of synthetic survey data, no study has systematically benchmarked both classification utility and […]
A privacy-preserving federated learning framework for generalizable CBCT to synthetic CT translation in head and neck
BackgroundCone-beam computed tomography (CBCT) has become a widely adopted modality for image-guided radiotherapy (IGRT). However, CBCT is characterized by increased noise, limited soft-tissue contrast, and artifacts. These issues result in unreliable Hounsfield unit (HU) values, which limits electron density estimation for direct dose calculation. These issues have been addressed by deriving synthetic CT (sCT) from […]
Assessing organisational and technological readiness for artificial intelligence implementation in the Ghana health service: a systematic review protocol
BackgroundArtificial intelligence (AI) holds transformative potential for public health systems in low- and middle-income countries. The Ghana Health Service (GHS), Ghana’s principal public health implementing agency, faces persistent workforce capacity gaps, fragmented digital infrastructure, and nascent data governance frameworks that collectively constrain AI adoption. No systematic review has specifically examined the multi-dimensional organisational and technological […]
Advancing women’s health through equity in quantitative sciences: promoting sex- and gender-based modeling in clinical trials and real-world studies
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Crisis support teams’ technological openness and learning attitudes toward the AI based virtual patient system crisis support VR
BackgroundAgainst the backdrop of escalating global humanitarian crises, innovative didactic simulations are becoming increasingly important. A promising alternative to traditional classroom-based didactics for learning psychological first aid (PFA) prior to humanitarian crises is to use generative artificial intelligence (GenAI)-based virtual patient (VP) systems. However, there is limited research on the use of GenAI-based VP systems […]