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[Atrial fibrillation screening-reading the P-wave]

Background Atrial fibrillation (AF) is frequently intermittent and may therefore remain undetected on a short resting electrocardiogram (ECG). At the same time, a sinus-rhythm ECG contains information on the underlying atrial substrate. Objective To review conventional and artificial intelligence (AI)-based ECG markers of an atrial risk phenotype and their potential role in targeted AF screening. Materials and methods Narrative appraisal of current consensus and guideline documents and of clinical, electrophysio…

Die Innere Medizin

Evidence-backed gain

Serum albumin is associated with immune-related hypothyroidism and treatment continuity in non-small cell lung cancer

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Generative AI versus physicians in diagnostic radiology: a systematic review and meta-analysis

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Explainable machine learning for identifying mild cognitive impairment in older adults with chronic diseases: Model development and temporal validation

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Rule-Based Versus Generative Extraction of Psychological Symptoms From Forensic Medical Certificates: A Feasibility Study in the French ORFeAD Network

Forensic medical certificates for victims of interpersonal violence describe psychological symptoms in unstructured prose, rarely explicit and requiring inference. To assess the feasibility of two extraction pipelines-rule-based and a locally served generative large language model-in a French multicentric forensic network, and to identify variables usable without human verification. 110 randomly selected 2021 certificates from 12 ORFeAD units were processed by both pipelines: rule-based (segmentation, lexicons,…

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Advancing Ultrasound Beamforming With Deep Learning: A Comprehensive Review of Methods, Datasets, Benchmarks, and Computational Challenges

Ultrasound imaging is a widely used diagnostic tool, and beamforming techniques are integral to its performance. Traditional methods such as delay-and-sum (DAS) and delay-multiply-and sum (DMAS) have limitations in terms of image quality and computational efficiency. Recently, deep learning approaches have shown significant promise in improving ultrasound beamforming, offering enhanced image resolution and quality, alongside potential for real-time processing. This review is aimed at providing a comprehensive ov…

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Applications and performance of imaging artificial intelligence in detecting and staging avascular necrosis of the femoral head: a systematic review and meta-analysis

Objective To evaluate the diagnostic accuracy of imaging artificial intelligence (AI) models for detecting avascular necrosis of the femoral head (AVNFH) and to examine whether diagnostic performance differs according to imaging modality, disease-stage focus, and validation strategy. Materials and methods In accordance with PRISMA-DTA, we conducted a systematic search in four main databases. Two independent reviewers evaluated the studies, extracted relevant data, and assessed the quality following the QUADAS-2…

Evidence-backed problem

After Jr NTR, Janhvi Kapoor condemns 'Chuttamalle' AI-generated explicit video: ‘Consent, choice and respect' are basic to humanity

Janhvi Kapoor has publicly addressed a manipulated AI video circulating online that misrepresents her image. The video was created using footage from her film Devara: Part 1 with Jr NTR. Kapoor described the circulation of such content as deeply violating and comparable to sexual assault. Actors from the Indian film industry have condemned the misuse of AI in this context.

Health

Development and Validation of Human-AI Collaborative Workflow in SNOMED CT Mapping of Bilingual Clinical Text

Systematized Nomenclature of Medicine-Clinical Terminology (SNOMED CT) is the principal international standard for semantic interoperability of clinical information, but mapping free-text clinical narratives to SNOMED CT concepts remains labor-intensive. We developed a large language model agent system for mapping bilingual clinical text to SNOMED CT concepts and evaluated its effect on mapping accuracy and efficiency within a human-AI collaborative workflow. We designed a three-module agent system comprising tr…

Science

Exploring Conversational Dynamics in Scientific and Pseudoscientific Health Communities on YouTube: Process Mining and Network Analysis Study

Background Social media platforms, particularly YouTube (Google LLC), are important sources of health information, but also significant vectors for misinformation and pseudoscience. While many studies analyze the content and sentiment of this information, the dynamic, sequential nature of user interactions, which can shape belief formation and community dynamics, remains poorly understood. Objective This study aimed to explore the applicability of network analysis and process mining techniques for identifying an…

Health

Generative artificial intelligence and commercial sexual exploitation of children: Implications for healthcare providers

Generative artificial intelligence (GAI) has created new avenues for the commercial sexual exploitation of children through the creation or manipulation of sexually explicit images using a child's likeness. Such images constitute a form of child sexual abuse material (CSAM), including when they are generated or manipulated without physical contact with the child. Because this abuse may occur without the child's awareness, it can complicate recognition, disclosure, and intervention while contributing to ongoing p…

Health

Artificial intelligence and digital technologies transforming neonatal respiratory assessment: a scoping review

Digital technologies and artificial intelligence (AI) have been increasingly incorporated into neonatal care, particularly in respiratory assessment. However, structured evidence regarding their clinical applications, performance, and limitations remains limited. This scoping review analyzed 35 studies published between 2019 and 2026 to map the use of digital technologies and AI in neonatal respiratory assessment. The findings showed that these approaches are mainly applied to predictive models, medical image an…

Science

Bias and Reliability of AI-Based Peer Review: A Comparative Study of ChatGPT and Claude Evaluating Scientific Abstracts

Background The use of artificial intelligence (AI) models as reviewers of scientific content raises concerns about potential biases related to author identity and about the reproducibility of their evaluations. We assessed whether AI-based reviewers exhibit gender or geographic bias and evaluated the reproducibility of their scoring of scientific abstracts. Methods We randomly selected 10 general internal medicine journals indexed in the Journal Citation Reports (impact factor ≥ 1.5). For each journal, five orig…

Policy

Recommendations for the Development and Implementation of Generative Artificial Intelligence Tools in Pediatric Clinical Care: Policy Statement

The integration of generative artificial intelligence (GenAI) into pediatric health care offers exciting opportunities alongside critical challenges. GenAI tools, like large language models (LLMs), show promise in several health care applications, including but not limited to clinical decision support, documentation, and medical education across a wide range of pediatric subspecialties. However, real-world validation remains limited, and concerns persist around accuracy, bias, reliability, sustainability, and du…

Health

Identifying incident medication-related osteonecrosis of the jaw and antiresorptive drug holidays using natural language processing on clinical notes in men and women prescribed bisphosphonates or denosumab for fracture prevention

Objective Medication-related osteonecrosis of the jaw (MRONJ) is a rare complication of antiresorptive therapy for osteoporosis, with risk potentially influenced by "drug holidays" around dentoalveolar procedures. MRONJ risk is higher in rheumatic diseases. Epidemiologic studies are limited by poor administrative code performance for MRONJ identification and lack of structured pharmacy data capturing drug holidays. We developed and validated a natural language processing (NLP) algorithm to classify MRONJ and det…

$Identifying incident medication-related osteonecrosis of the jaw and antiresorptive drug holidays using natural language processing on clinical notes in men and women prescribed bisphosphonates or denosumab for fracture prevention$