± HEALTH Large language models (LLMs) are artificial intelligence (AI) tools specifically trained to process and gener…+ 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…
TruaceTracing the truth around AIMonday, September 14, 2026
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1046 published stories · page 39 of 70

Evidence-backed gain

Performance of artificial intelligence in the collection of patient history in general practice

Automating administrative tasks, such as compiling a patient's medical history, could help general practitioners in their daily work. AI performance has improved in recent decades, but skepticism among professionals limits its use in medical practice, due to fears of gaps and biases. This study attempts to evaluate the effectiveness of AI in recording patient histories compared to general practitioners. Cross-sectional study. SITE: Online study in France. French general practitioners recruited online. We compare…

Atención Primaria · Health

Performance of artificial intelligence in the collection of patient history in general practice
Harnessing data science and artificial intelligence to advance implementation research and practice
Both readings

Harnessing data science and artificial intelligence to advance implementation research and practice

Implementation science aims to bridge the gap between research evidence and routine health care practice by understanding and optimizing the integration of evidence-based interventions. In this paper, we identify seven persistent challenges limiting implementation progress, including (1) overwhelming volume of implementation materials (e.g., reports, interviews, surveys); (2) contextual variability; (3) complex interactions between contextual factors, interventions, and outcomes; (4) interest holder engagement c…

Science
Can platform literacy protect vulnerable young people against the risky affordances of social media platforms?
Evidence-backed gain

Can platform literacy protect vulnerable young people against the risky affordances of social media platforms?

A qualitative study of young people with mental health difficulties sought to understand their digital experiences and identify whether their digital literacy helps them cope with online problems. The findings reveal how young people’s encounters with extreme online risk are amplified by platforms’ promotion of trending and viral content and intensified through the personalisation of content that can ‘trigger’ individual vulnerabilities. We conceptualise these twin processes in terms of risky affordances and sho…

Health

Optimizing Treatment Strategies in the Bipolar Disorder Spectrum With Classical AI Approaches: Systematic Review of Performance, Bias, and Clinical Applicability

Bipolar disorder (BD) is a complex and heterogeneous psychiatric condition, characterized by fluctuating clinical courses that affect approximately 1%-2% of the global population in their lifetime. Despite pharmacological advances, treatment response varies significantly among patients, making the identification of individualized treatment strategies a major challenge. Artificial Intelligence (AI), through its classical approaches, has emerged as a powerful tool in precision psychiatry to identify subtle pattern…

Health
Optimizing Treatment Strategies in the Bipolar Disorder Spectrum With Classical AI Approaches: Systematic Review of Performance, Bias, and Clinical Applicability

DynStabNet: A Deep Learning Framework for Fast Dynamical Stability Prediction of Crystal Structures

Semiconductor materials are widely used in electronic, optoelectronic, and energy applications. While DFT-based phonon calculations provide highly accurate assessments for dynamical stability of structures, their prohibitive computational cost poses a significant bottleneck for large-scale materials screening. Herein, we develop DynStabNet, an E(3)-equivariant graph neural network (E3GNN) framework that learns dynamical stability from phonon-informed data, enabling rapid prediction without the need for explicit…

Science
DynStabNet: A Deep Learning Framework for Fast Dynamical Stability Prediction of Crystal Structures

A Supervised Fine-Tuned Large Language Model for Lifestyle Management in Patients With Prostate Cancer: Development and Evaluation Study

Lifestyle interventions for patients with prostate cancer have been shown to improve treatment adherence and quality of life. However, there remains a lack of large language models (LLMs) capable of delivering individualized and professional lifestyle recommendations under clearly defined medical safety boundaries and controlled evidence sources. This study aimed to develop and evaluate a supervised fine-tuned LLM-PCaPLMM_SFT (Prostate Cancer Patient Lifestyle Management Model via Supervised Fine-Tuning)-to supp…

Health
A Supervised Fine-Tuned Large Language Model for Lifestyle Management in Patients With Prostate Cancer: Development and Evaluation Study

Multiturn Large Language Model-Based Conversational Agents for Patients With Cancer and Caregivers: Scoping Review

Large language model (LLM)-based conversational agents are increasingly used in health care, yet their capacity to support genuine multiturn dialogue remains underexplored. In oncology, where patients and caregivers experience complex informational and emotional needs throughout the disease trajectory, conversational agents may support information provision, symptom consultation, and emotional assistance. However, research specifically examining multiturn conversational agents designed for patients with cancer a…

Health
Multiturn Large Language Model-Based Conversational Agents for Patients With Cancer and Caregivers: Scoping Review

Enhancing objective structured clinical examination performance through an artificial intelligence virtual patient: a proof-of-concept study

The application of artificial intelligence (AI) in simulating detailed patient-doctor interactions for objective structured clinical examinations (OSCEs) remains emerging. This study aimed to evaluate an AI virtual patient (AIVP) innovation designed to support medical education through interactive patient simulations and feedback. This prospective mixed-methods pilot recruited final-year medical students during their critical care term. Two cohorts were examined: a volunteer AIVP group (n = 43) and an educationa…

Health
Enhancing objective structured clinical examination performance through an artificial intelligence virtual patient: a proof-of-concept study

Can AI assist in reducing diagnostic error? A narrative review

Diagnostic error, defined as missed, wrong, or delayed diagnoses or those not communicated to patients, is common, affecting 5-10 % of hospital admissions and clinic visits. Such errors cause patient harm in up to 1 in 100 of such encounters and account for 10 % of all hospital deaths and serious adverse events. About 80 % of diagnostic errors are potentially preventable, most resulting from flaws in clinician reasoning in formulating and testing diagnostic hypotheses. The advent of artificial intelligence (AI),…

Health
Can AI assist in reducing diagnostic error? A narrative review

Deezer says AI music now makes up half of all daily song uploads.

The music streaming platform receives almost 90,000 AI-generated tracks each day, a jump from the 75,000 it last reported in April. Using its AI music detection tool, Deezer now says it will take down AI tracks “used to generate fraudulent streams,” in addition to those that haven’t been streamed in six months or more. [Link: AI Music Tops 50% of Daily Uploads on Deezer | https://newsroom-deezer.com/2026/07/ai-music-exceeds-50-percent-daily-uploads-deezer/ | Deezer Newsroom]

Media & Arts
Deezer says AI music now makes up half of all daily song uploads.