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Diagnostics & Imaging · 155 stories · page 1 of 11

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LLM-supported self-diagnosis and self-treatment of familial Mediterranean fever: a case report

Large language models (LLMs) are increasingly being used by patients to seek explanations for persistent or unexplained symptoms. However, their impact on real-world diagnostic pathways and patient behavior remains poorly understood. We report the case of a 34-year-old male of Egyptian origin with recurrent episodes of fever, severe migratory abdominal pain, arthralgia, myalgia, and intermittent erythematous skin lesions since early childhood. Despite almost 3 decades of extensive investigations, no unifying dia…

EULAR Rheumatology Open

Evidence-backed gain

An assisted telemedicine model with digital diagnostics and artificial intelligence-supported clinical decision in hard-to-reach rural communities: a community-based mixed-methods study from Rajasthan, India

Evidence-backed problem

Artificial Intelligence in Eye Disease: A Systematic Review of Screening, Diagnosis, Prognosis, Treatment-Response Prediction, and Clinical Decision Support

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From Algorithm to Care: AI-Assisted Glaucoma Screening in Real-World Settings

Evidence-backed gain

Graph theory-based machine learning for automated fibromyalgia diagnosis using fMRI during an emotional task

Background Fibromyalgia (FM) is a multifaceted chronic pain disorder presenting with pain throughout the musculoskeletal system, alongside chronic fatigue,sleep disturbances, and cognitive impairments. Current diagnostic criteria primarily rely on symptom questionnaires, with no specific laboratory markers or definitive tests, making diagnosis subjective and often delayed. Moreover, the overlap with other central pain syndromes further complicates accurate diagnosis. Neuroimaging studies, particularly functional…

Evidence-backed gain

Cost-Effectiveness of AI in Breast Cancer Screening and Lung Cancer Diagnostics: A Case Study From Costa Rica

Objectives This study evaluated the cost-effectiveness of integrating artificial intelligence (AI) into breast and lung cancer diagnostic workflows in Costa Rica, addressing the scarcity of health economic evidence for AI adoption in low- and middle-income countries and focusing on context-specific systemic barriers. Methods Two state-transition Markov models compared AI-assisted workflows (AI as a first reader) with conventional radiologist-only strategies over a 10-year horizon. AI-supported mammography screen…

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Artificial Intelligence applied to surgical pathology in the management of cutaneous melanoma

Surgical pathology remains the cornerstone for the diagnosis, staging and prognostic stratification of cutaneous melanoma. The emergence of digital pathology and artificial intelligence (AI), notably deep learning, is transforming this field. Convolutional neural networks trained on large repositories of digitised histological slides demonstrate diagnostic capabilities comparable, and in specific tasks superior, to board-certified dermatopathologists. Current applications encompass the automated classification o…

Evidence-backed gain

Artificial Intelligence for Cardiac Ischemia Detection: A Review of Biosensor, Biomarker, and Imaging Applications

Ischemic heart disease is the leading cause of global mortality, yet accurate and timely detection remains constrained by incomplete signal capture, noise, operator dependence, and imperfect reference standards. Artificial intelligence (AI) may enhance cardiovascular sensing by extracting latent diagnostic information from routinely acquired signals. This narrative review examines AI-enabled approaches to ischemia detection across three sensing modalities: the electrocardiogram as a bioelectric sensor, cardiac t…

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Cost-effectiveness of community-based artificial intelligence screening for retinopathy of prematurity

Background Retinopathy of prematurity (ROP) is one of the leading causes of childhood blindness globally, but particularly in middle-income countries, where neonatal survival has improved faster than access to specialist ophthalmic care. Although telemedicine and artificial intelligence (AI)-assisted screening show promise for improving access to ROP screening, their economic value within decentralised health systems remains uncertain. To explore this issue, we evaluated the cost-effectiveness of community-based…

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Diagnos Inc recalls an AI-enabled medical device

CARA (Computer Assisted Retinal Analysis), Product ID: +B543CARA0/$$+7V4.7.2/16D202111179 Recall reason: Retinal analysis system software has some features, based on artificial intelligence, that potentially lack appropriate market approval, so it is recommended to use a specific prior software version.

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The ethical and regulatory framework of medical artificial intelligence (AI) system’s behavioral performance for image-based diagnostics: An ethical evaluation of the International and European Union

Author summary The use of Artificial Intelligence (AI) in diagnostics based on medical images is increasing. AI can automatically analyze images, quickly detect patterns, and support physicians. However, using this technology in patient care raises ethical challenges and requires ethical and regulatory protection. In April and May 2025, we screened official documents to identify ethical challenges of the ethical and regulatory framework of the diagnostic technology’s behavior on the international and European Un…

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Can General-purpose Multimodal AI Reliably Measure Cobb Angles? A Head-to-head Diagnostic Agreement Study of GPT-5.1 and Gemini 3.1 Pro in Adolescent Idiopathic Scoliosis

General-purpose multimodal artificial intelligence (AI) models can interpret radiographs through natural-language prompts, but their quantitative agreement and anatomical traceability in adolescent idiopathic scoliosis remain uncertain. We compared GPT-5.1 and Gemini 3.1 Pro with a joint expert-consensus reference on 125 anonymized standing coronal whole-spine radiographs. Each model evaluated each image once in an independent chat session using the same standardized prompt; only the first response was retained.…

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Automating Injury Severity Score Calculation From Free-Text Discharge Diagnoses Using Domain-Specific Retrieval-Augmented Large Language Models: Retrospective Validation Study

Background: Trauma registries are crucial for evaluating the prognosis of injuries and the quality of trauma care. However, the calculation of Injury Severity Score (ISS) remains a predominantly manual process, which is labor-intensive, potentially error-prone, and difficult to scale. Automating this process is a critical step toward enhancing the efficiency and quality of trauma registry data. Objective: This study conducts a feasibility test on the use of large language models (LLMs) to automatically calculate…

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Comparing Diagnostic Ability of Two Off-the-Shelf Large Language Models with That of Endodontists for Teeth Requiring Initial Root Canal Treatment: A Multicenter Retrospective Investigation

Introduction: Despite growing interest in large language models (LLMs) for endodontic diagnosis, prior studies have used simulated cases, examination formats, or small selected series. This multicenter retrospective study compared the diagnostic accuracy of ChatGPT-5.2 and Gemini 3.0 with that of calibrated endodontists across 645 teeth requiring initial root canal treatment. Methods: Cases were evaluated across four endpoints: pulpal diagnosis, periapical diagnosis, treatment planning, and case difficulty. Stan…

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Multimodal artificial intelligence in dental diagnosis: influence of reasoning depth and domain-specific medical model on diagnostic performance

Large language models are increasingly explored as clinical decision-support tools, but the relationship between configurable reasoning effort and multimodal diagnostic performance remains unclear. This study evaluated the association between API-configured reasoning effort and multimodal oral and dental diagnostic performance in GPT-5 and compared its outputs with those of the compact open-weight medical-domain model MedGemma-1.5-4b-it. Eight anonymized multimodal case reports representing dental trauma, odonto…