Health

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HealthEvidence-backed problem

Hallucinating with AI: Distributed Delusions and “AI Psychosis”

Abstract There is much discussion of the false outputs that generative AI systems such as ChatGPT, Claude, Gemini, DeepSeek, and Grok create. In popular terminology, these have been dubbed “AI hallucinations”. However, deeming these AI outputs “hallucinations” is controversial, with many claiming this is a metaphorical misnomer. Nevertheless, in this paper, I argue that when viewed through the lens of distributed cognition theory, we can better see the dynamic ways in which inaccurate beliefs, distorted memories…

Philosophy & Technology

Evidence-backed gain

Multimodal Large Language Models in Health Care: Applications, Challenges, and Future Outlook

Both readings

The EU Artificial Intelligence Act (2024): Implications for healthcare

Both readings

Artificial Intelligence-Driven Development and Characterization of Nanomedicine

Evidence-backed problem

A framework for human evaluation of large language models in healthcare derived from literature review

With generative artificial intelligence (GenAI), particularly large language models (LLMs), continuing to make inroads in healthcare, assessing LLMs with human evaluations is essential to assuring safety and effectiveness. This study reviews existing literature on human evaluation methodologies for LLMs in healthcare across various medical specialties and addresses factors such as evaluation dimensions, sample types and sizes, selection, and recruitment of evaluators, frameworks and metrics, evaluation process,…

Both readings

“It happened to be the perfect thing”: experiences of generative AI chatbots for mental health

The global mental health crisis underscores the need for accessible, effective interventions. Chatbots based on generative artificial intelligence (AI), like ChatGPT, are emerging as novel solutions, but research on real-life usage is limited. We interviewed nineteen individuals about their experiences using generative AI chatbots for mental health. Participants reported high engagement and positive impacts, including better relationships and healing from trauma and loss. We developed four themes: (1) a sense of…

Evidence-backed gain

Revolutionizing healthcare and medicine: The impact of modern technologies for a healthier future—A comprehensive review

The increasing integration of new technologies is driving a fundamental revolution in the healthcare sector. Developments in artificial intelligence (AI), machine learning, and big data analytics have completely transformed the diagnosis, treatment, and care of patients. AI-powered solutions are enhancing the efficiency and accuracy of healthcare delivery by demonstrating exceptional skills in personalized medicine, early disease detection, and predictive analytics. Furthermore, telemedicine and remote patient m…

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…

Health

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

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

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

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

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

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…