Prevention of medical errors

Evaluating AI-Mediated Health Communication via Large Language Model-Based Frequently Asked Questions Rewriting to Foster Clinical Trial Participation: Comparative Survey Study.

BACKGROUND: Effective communication about clinical trials is essential, as low enrollment undermines scientific validity and contributes to health care inequities. However, recruitment remains a persistent challenge, particularly among older adults, minority populations, and individuals with limited health literacy. Although large language models (LLMs) show promise in understanding and generating...

Multi-modal personalized federated learning with adaptive differential privacy for medical image classification and a privacy-preserving approach.

Deep learning on medical images classification intervention needs to use large data on multi-institutional datasets but privacy laws inhibit sharing of data (GDPR, HIPAA). Federated Learning (FL) facilitates collaborative training without data transfer; until now, the known methods can only address privacy, personalisation, and accuracy not at the same time in a multi-modal environment. We present...

What it takes to be great: ChatGPT's top 5 descriptors of great surgeons by race, ethnicity, gender, and sexual orientation.

BACKGROUND: Diversity of providers in medical teams improves team communication, increases care for underserved populations, enhances patient complian...

Federated learning with swarm intelligence for efficient and secure medical image analysis.

Collaborative learning in healthcare faces challenges, including strict regulations and fragmented data. This research introduces a federated learning...

An ML-driven framework for continuous wearable health surveillance and energy-efficient communication.

Existing wireless body area network (WBAN) communication schemes often depend on fixed event assumptions, which results in redundant transmissions, po...

Alignment of Lived Experience Questions with the Medical Literature in Bipolar Disorder: A Topic Modelling Approach: Adéquation entre les questions relatives à l'expérience vécue et la littérature médicale concernant le trouble bipolaire : Une approche de modélisation de sujets.

ObjectiveThe priorities of people with mental health challenges should be reflected in the research conducted on their behalf. Quantifying alignment o...

[Use of artificial intelligence for next-gen anamnesis and communication in orthopedics & trauma surgery : From chatbots to ambient intelligence].

BACKGROUND: Against the backdrop of increasing patient volumes, rising case complexity, and physicians' limited time, AI-driven systems for anamnesis,...

A Guide to Constructing Indigenous Statistical Spaces for Prevention Science Research.

Artificial intelligence (AI)-powered computational methods, such as machine learning and natural language processing, are increasingly applied in deat...

VFLING: Vertical Federated Learning for Multi-Omics Data Integration with Graphs.

Modern machine learning models leveraging multi-omics data face significant privacy challenges due to the sensitive nature of patient information. Com...

Communication-Based Teaching on Childhood Obesity and the Planetary Health Diet in Medical Education: Proof-of-Concept Study Comparing 4 Information Sources.

BACKGROUND: Childhood obesity constitutes a complex medical and psychosocial challenge that requires both nutritional knowledge and sensitive, relatio...

Older adults' perceptions of artificial intelligence in healthcare: an exploratory quantitative analysis.

BACKGROUND AND OBJECTIVES: Artificial intelligence (AI) has the potential to improve healthcare outcomes. There is limited literature regarding older ...

The detectability paradox: bilingual medical report generation with open-weight models and the limits of human oversight.

OBJECTIVES: The automation of medical report generation using large language models (LLMs) could significantly reduce physicians' documentation burden...

Research on interpretable machine learning modeling and spatial prediction of cross-landform landslide disaster mechanism: A case study of Shaanxi Province.

The differential understanding of the landslidetriggering mechanisms across various geomorphic units is vital for enhancing regional disaster preventi...

Imaging and AI in tertiary prevention of lung cancer: Narrative review and clinical perspectives.

OBJECTIVE: To provide a structured narrative review of current evidence and future directions for artificial intelligence (AI) applications in the ter...

Ethical risk prevention in client generative artificial intelligence (genAI) use: Applying the primary risk-management model.

As clients increasingly use generative artificial intelligence for emotional support, psychologists now deal with unfamiliar ethical challenges that g...

Why We Need Patients and Community at the Center of AI Health Communication Research.

Holderried and colleagues tested whether artificial intelligence (AI)-generated, patient-centered information can help people understand what they nee...

Impact of a Prototype Combining Recommender Functionality With Structured Documentation on Operator Performance in Calls to Medical Communication Centers: Quasi-Experimental Feasibility Study.

BACKGROUND: Management of contacts to medical communication centers relies heavily on clinical judgment, contextual understanding, and communication s...

A step-by-step guide for implementation of virtual surgical applications and patient data centralization: practical experience and lessons learned.

BACKGROUND: The expansion of digitalization in the pre-, intra- and post-operative surgical phases allow the development and integration of advanced t...

Research on depression diagnosis method based on multi-scale analysis of frontal lead EEG.

BACKGROUND: Depression is one of the most prevalent mental disorders globally, severely affecting individuals' emotional, cognitive, and physical func...

Machine learning approaches to distinguish bipolar disorder from borderline personality disorder: a scoping review.

BACKGROUND: Borderline personality disorder (BPD) and bipolar disorder (BD) are debilitating psychiatric illnesses with significant rates of misdiagno...