IntroductionHigh-precision liver and tumor segmentation is a cornerstone of digital oncology, yet its clinical deployment remains constrained by two persistent challenges: the scarcity of pixel-level annotations and severe performance degradation under cross-center domain shift. Although few shot learning offers a promising direction for data-efficient modeling, existing approaches relying solely on visual similarity often fail to […]
Automated emotion recognition via video-based semantic embeddings
IntroductionAutomated emotion recognition systems often rely on acted datasets and categorical models that miss the nuance of spontaneous affect.MethodsThis work assembled a large corpus of authentic facial emotion expressions from naturalistic outpatient psychotherapy sessions, annotated with free-text descriptions by human labelers. These descriptions were embedded in a 768-dimensional semantic space using a fine-tuned German Sentence-BERT […]
Best practices and challenges in executing large scale pilots for eHealth deployment and managing innovation: the GATEKEEPER experience
The large-scale deployment of digital health solutions requires robust operational frameworks capable of coordinating heterogeneous settings, diverse stakeholders, and complex technical infrastructures. However, actionable guidance for executing federated, multinational eHealth pilots remains limited in the implementation literature. Methods: Using a mixed-methods approach, including iterative focus groups, co-creation sessions, and a Delphi study, we developed and […]
Beyond accuracy: evaluating the operational feasibility and diagnostic yield of CAD4TB vs. Timika score for scalable TB screening in low-resource settings
Artificial intelligence has shown promise in enhancing tuberculosis care, but its use in resource-limited settings like Indonesia remains underexplored. This cross-sectional retrospective single-centre study evaluates the diagnostic performance of CAD4TB in screening Indonesian patients suspected of tuberculosis using chest x-ray (CXR) images, comparing its efficacy to the Timika score assessed by experts. We analyzed CXR […]
Beyond the digital divide: multi-group SEM examination of socioeconomic status, mHealth utilization, and urban-rural physical activity disparities in Indonesia
BackgroundMobile health (mHealth) technological innovations are now widely being promoted as a scalable solution to the rising problem of obesity. Unfortunately, there is a dearth of empirical research on the extent to which mHealth utilization is associated with acceptance disparities in emerging economies.ObjectiveThis work explores the associations among socioeconomic status (SES), urban-rural differences, mHealth utilization, […]
Optimizing drug combinations to resurrect the potency of failed antibody therapy against emerging COVID-19 variants using IDentif.AI
IntroductionSince the outbreak of the COVID-19 pandemic, extensive efforts including vaccine and drug development have been accentuated to address the emergence of SARS-CoV-2 variants. The rising variants and subvariants made early discoveries in effective treatment strategies less relevant and potent. For instance, multiple therapeutics like Evusheld are no longer effective against current variants and therefore […]
Exploring public perceptions of artificial intelligence in bereavement support: a qualitative study of griefbots
BackgroundArtificial intelligence technologies designed to simulate deceased loved ones, often referred to as griefbots, are emerging as a novel form of bereavement support. Although such technologies may offer emotional comfort and a sense of continued connection with the deceased, they also raise complex psychological, ethical, and societal concerns. This study aimed to explore public perceptions […]
Explainable and interpretable models for predicting early-onset hypertension in the Tlalpan 2020 cohort
BackgroundEarly-onset hypertension results from complex interactions among demographic, lifestyle, metabolic, and psychosocial factors. While machine learning models can predict hypertension with relative accuracy, their lack of interpretability limits their clinical utility.MethodsUsing a nested case-control design based on the Tlalpan 2020 prospective cohort, a 10-year study of clinically healthy adults in Mexico City, this study applies […]
Mapping Practice-Based Signals of Generative AI in Psychiatric Care: Qualitative Study of Korean Psychiatrists’ Experiences, Interpretations, and Implementation Priorities
Background: Generative artificial intelligence (GenAI) has increasingly entered psychiatric practice through patient-facing chatbots, self-help tools, and clinician-facing workflow support. Although prior research has examined clinicians’ attitudes, readiness, and anticipated use cases, less is known about how frontline encounters with GenAI shape psychiatrists’ interpretations and implementation priorities. Health care foresight also remains methodologically underdeveloped and has […]
Confidence Measurement Metrics in Multimodal Large Language Models for Ultrasound-Based Radiology Cases: Comparative Evaluation Study of Self-Reported, Consistency-Based, and Hybrid Methods
Background: Large language models (LLMs) require specialized methodologies to quantify model confidence for safe deployment in health care systems; however, there is a lack of established methods for confidence assessment. Objective: This study aimed to evaluate confidence metrics for multimodal LLMs interpreting ultrasound-based radiology cases and to compare self-reported, consistency-based, and hybrid methods. Methods: From […]
DriveSurge Hijacks Thousands of Sites for ClickFix, FakeUpdate Attacks
A sneaky, wide-scale IAB operation uses a malicious traffic distribution system (TDS) to redirect visitors of trusted websites to ones that deliver malware.
China Uses Dual-Method Cyberattack on Czech Orgs
China is stealing data from high-value targets via a sneaky, double-layer spear-phishing campaign that includes the Azureveil malware.