+ HEALTH Background Discharge letters are essential for continuity of care, yet patients often misunderstand their con…± HEALTH Hematoxylin and Eosin (H&E) glass slide preparation is fundamental to histopathology. Pathologists' expertise…+ CLIMATE Traditional soil heavy metal risk assessments suffer from fragmented indices and poor logical integration. Co…± HEALTH Background Neonatal pneumothorax can progress rapidly, yet detection on supine chest radiographs remains chal…+ HEALTH T cell exhaustion has widespread implications for the progression and treatment of chronic diseases including…+ HEALTH Background Standard pulmonary arterial hypertension (PAH) risk models may not fully apply to PAH associated w…+ HEALTH Objectives To map and synthesize the scientific evidence regarding the use of Augmented Reality (AR) and Mixe…± HEALTH Objective To examine whether the outputs of machine learning algorithms designed to predict risk of cardiovas…
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Evidence-backed gain

The Impact of Chatbots on Adolescent Mental Health Development: A Comprehensive Literature Review

The integration of artificial intelligence (AI) chatbots in adolescent mental health care represents a transformative shift in how digital interventions address psychological well-being among young populations. This comprehensive review synthesizes evidence examining the multifaceted impact of chatbot technology on adolescent mental health development. A systematic search was conducted across PubMed, PsycINFO, Web of Science, and Scopus databases using terms related to chatbots, conversational agents, adolescent…

Journal of Multidisciplinary Healthcare · Health

The Impact of Chatbots on Adolescent Mental Health Development: A Comprehensive Literature Review
Mapping Caregiver Needs to AI Chatbot Design: Strengths and Gaps in Mental Health Support for Alzheimer's and Dementia Caregivers
Both readings

Mapping Caregiver Needs to AI Chatbot Design: Strengths and Gaps in Mental Health Support for Alzheimer's and Dementia Caregivers

Family caregivers of individuals with Alzheimer’s Disease and Related Dementia (AD/ADRD) face significant emotional and logistical challenges that place them at heightened risk for stress, anxiety, and depression. Although recent advances in generative AI—particularly large language models (LLMs)—offer new opportunities to support mental health, little is known about how caregivers perceive and engage with such technologies. To address this gap, we developed Carey, a GPT-4o–based chatbot designed to provide info…

Health
Data-Centric Foundation Models in Computational Healthcare: A Survey
Both readings

Data-Centric Foundation Models in Computational Healthcare: A Survey

The advent of foundation models (FMs) as an emerging suite of AI techniques has struck a wave of opportunities in computational healthcare. The interactive nature of these models, guided by pre-training data and human instructions, has ignited a data-centric AI paradigm that emphasizes better data characterization, quality, and scale. In healthcare AI, obtaining and processing high-quality clinical data records has been a longstanding challenge, encompassing data quantity, annotation, patient privacy, and ethics…

Health
Artificial Intelligence (AI) Applications in Drug Discovery and Drug Delivery: Revolutionizing Personalized Medicine
Evidence-backed gain

Artificial Intelligence (AI) Applications in Drug Discovery and Drug Delivery: Revolutionizing Personalized Medicine

Artificial intelligence (AI) encompasses a broad spectrum of techniques that have been utilized by pharmaceutical companies for decades, including machine learning, deep learning, and other advanced computational methods. These innovations have unlocked unprecedented opportunities for the acceleration of drug discovery and delivery, the optimization of treatment regimens, and the improvement of patient outcomes. AI is swiftly transforming the pharmaceutical industry, revolutionizing everything from drug developm…

Health
Sex differences in CT-FFR of myocardial bridging with or without atherosclerosis: an AI-based quantitative study
Both readings

Sex differences in CT-FFR of myocardial bridging with or without atherosclerosis: an AI-based quantitative study

Background: Myocardial bridging (MB) is a prevalent coronary anomaly with potential links to major adverse cardiac events. While computed tomography-derived fractional flow reserve (FFRCT) offers a non-invasive functional assessment, current evidence predominantly treats MB as a homogeneous entity, overlooking potential sex differences in hemodynamic impact. Existing studies often fail to distinguish between isolated MB and MB with concomitant atherosclerosis, and rarely employ sex-stratified analyses. This stud…

Health
Real-World Evidence Synthesis of Digital Scribes Using Ambient Listening and Generative Artificial Intelligence for Clinician Documentation Workflows: Rapid Review
Both readings

Real-World Evidence Synthesis of Digital Scribes Using Ambient Listening and Generative Artificial Intelligence for Clinician Documentation Workflows: Rapid Review

Background: As physicians spend up to twice as much time on electronic health record tasks as on direct patient care, digital scribes have emerged as a promising solution to restore patient-clinician communication and reduce documentation burden-making it essential to study their real-world impact on clinical workflows, efficiency, and satisfaction. Objective: This study aimed to synthesize evidence on clinician efficiency, user satisfaction, quality, and practical barriers associated with the use of digital scr…

Health
Artificial Intelligence for Cervical HPV Infection and Lesion Screening: A Cross-Sectional Analysis of Its Application Potential and Patient Satisfaction
Both readings

Artificial Intelligence for Cervical HPV Infection and Lesion Screening: A Cross-Sectional Analysis of Its Application Potential and Patient Satisfaction

OBJECTIVE: This cross-sectional study aimed to explore the application potential of artificial intelligence (AI) in screening and diagnosing cervical human papillomavirus (HPV) infection and lesions, and to assess patient satisfaction with the current diagnostic and therapeutic process as well as their unmet needs. METHODS: An online cross-sectional survey was conducted via the Questionnaire Star platform, and 308 valid responses were collected. Descriptive statistics were used to summarize participants' demogra…

Health

Implementation of an AI-driven hierarchical medical system for chronic disease management: ethical framework, resource optimization, and effectiveness evaluation

Objective The aim of this study was to assess the integration pathways and ethical frameworks associated with the use of artificial intelligence (AI) within hierarchical medical systems for chronic disease management, and quantitatively assess its impact on healthcare resource allocation efficiency and treatment outcomes. Methods A four-dimensional closed-loop model comprising data collection, decision intervention, resource scheduling, and outcome feedback was used to structure the system. This analysis incorpo…

Health
Implementation of an AI-driven hierarchical medical system for chronic disease management: ethical framework, resource optimization, and effectiveness evaluation

Skyer: a novel benchmark for evaluating the effectiveness of large language models in emergency department triage

OBJECTIVES: Emergency department (ED) overcrowding causes diagnostic challenges, prolonged wait times, and impairs appropriate triage, often due to human error and fatigue. Large language models can assist ED staff in triage, improving patient care by mitigating these problems. METHODS: We designed an evaluation method (Skyer benchmark) to assess fifteen large language models, including DeepSeek-R1 (70B, 7B), ChatGPT versions (4, 4.5-preview), Gemini iterations (1.5-pro, 2.0-Pro-experimental, 2.5_03-25, 2.5_05-0…

Health
Skyer: a novel benchmark for evaluating the effectiveness of large language models in emergency department triage

Performance evaluation of five major large language models in tuberculosis Q&A systems: A multidimensional assessment of readability, quality, and reliability

Background: Pulmonary tuberculosis (TB) is a chronic infectious disease that burdens patients and public health systems. Limited reach of traditional education and uneven online information may undermine patients' understanding, adherence, and trust. Large language models (LLMs) show promise for TB health education, but systematic evaluation is lacking. Objective: To evaluate five large language models in pulmonary tuberculosis Q&A (Question and Answer) scenarios and examine the effects of different large langua…

Health
Performance evaluation of five major large language models in tuberculosis Q&A systems: A multidimensional assessment of readability, quality, and reliability

Mapping artificial intelligence integration in objective structured clinical examinations: A scoping review

INTRODUCTION: Objective Structured Clinical Examinations (OSCEs) are widely used to assess clinical competence, but face challenges related to examiner workload, scoring variability, delayed feedback, and resource demands. Although AI may address these constraints and support precision medical education, the evidence remains fragmented. This scoping review maps AI applications in OSCEs. METHODS: We followed PRISMA-ScR. We searched MEDLINE, Scopus, Embase, Web of Science, ERIC, LILACS, and IEEE Xplore from incept…

Health
Mapping artificial intelligence integration in objective structured clinical examinations: A scoping review

Combining pathology artificial intelligence and genomic biomarkers to refine long-term postprostatectomy outcome prediction

BACKGROUND: A multimodal AI (MMAI) model has been validated in prostate biopsy specimens to guide treatment intensification in men receiving radiation. The MMAI has been explored to an extent for prostatectomy patients and has not yet been examined in relation to established genomic scores. METHODS: We applied the MMAI biopsy model to a tissue microarray (TMA) of 424 prostatectomy cases with long-term follow-up. MMAI scores were derived from digitized pathology images and clinical variables. Associations with bi…

Health
Combining pathology artificial intelligence and genomic biomarkers to refine long-term postprostatectomy outcome prediction

Improving turnaround times with artificial intelligence in microbiology

This dual-center study evaluated the impact of artificial intelligence (AI) on urine culture turnaround times in Canadian diagnostic laboratories using microbiology laboratory automation. Data were collected before and after the implementation of PhenoMATRIX (PM), an AI-based software that provides continuous culture sorting and result interpretation support. In both a low-volume tertiary care hospital and a high-volume community laboratory, PM enabled earlier availability of interpretable results; however, redu…

Health
Improving turnaround times with artificial intelligence in microbiology

Artificial Intelligence for Evidence Synthesis of Emerging Biologics to Improve Skeletal Health in Osteogenesis Imperfecta: Systematic Review and Meta-Analysis

Background: Osteogenesis imperfecta (OI) is a rare genetic disorder characterized by bone fragility and recurrent fractures. Emerging biologics demonstrate promise by targeting bone-remodeling pathways, yet evidence for their efficacy and safety remains fragmented and heterogeneous, and no prior systematic review in OI has incorporated artificial intelligence (AI) to synthesize it. Objective: This study aims to systematically evaluate the efficacy and safety of novel biologics in patients with OI using an AI-ass…

Health
Artificial Intelligence for Evidence Synthesis of Emerging Biologics to Improve Skeletal Health in Osteogenesis Imperfecta: Systematic Review and Meta-Analysis

Beyond EuroSCORE II: is artificial intelligence ready to redefine risk stratification in cardiothoracic surgery?

Risk stratification is central to contemporary cardiothoracic surgical practice, guiding patient selection, perioperative planning, informed consent, and benchmarking of outcomes across institutions. Established models such as European System for Cardiac Operative Risk Evaluation II and the Society of Thoracic Surgeons risk score remain widely used because they are validated, interpretable, and embedded within routine clinical workflows. However, their static structure and reliance on predefined variables may li…

Health
Beyond EuroSCORE II: is artificial intelligence ready to redefine risk stratification in cardiothoracic surgery?