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Consensus statement on the application of artificial intelligence in osteoporosis screening and management: perspectives from the Asia-Pacific region.

UNLABELLED: Osteoporosis is a major and growing health concern in the Asia-Pacific region, y et it remains widely underdiagnosed and undertreated due to limited access to dual-energy X-ray absorptiometry (DXA) in many areas. Artificial intelligence (AI) offers new opportunities to improve osteoporosis screening and management, but unvalidated tools pose risks of inconsistent care. This consensus was developed to provide regionally harmonized guidance on the safe, effective, and equitable use of AI in osteoporosis care. PURPOSE: The aim of this work was to establish expert consensus recommenda…

Data-derived Identity Verification as a principle for the dissemination, harmonization, and artificial intelligence reuse of sensitive biomedical data.

OBJECTIVES: To facilitate responsible biomedical data sharing, large-scale data harmonization, and cutting-edge artificial intelligence (AI) applications by augmenting controlled-access data dissemination models (DDMs) with Data-derived Identity Verification (DIVe). MATERIALS AND METHODS: We developed a watermarking-based DIVe system that embeds a cryptographically verifiable and traceable identity within each data file. This system was deployed for the Artificial Intelligence Ready and Exploratory Atlas for Diabetes Insights Consortium and currently watermarks a 3.8TB multimodal dataset for …

The Rise in Artificial Intelligence and Machine Learning Models to Screen for Cleft-Related Velopharyngeal Dysfunction: A Systematic Review.

ObjectiveTo systematically review literature on the use of artificial intelligence (AI) and machine learning (ML) models for detecting velopharyngeal dysfunction (VPD) in patients with cleft palate.DesignSystematic review conducted in accordance with PRISMA guidelines (PROSPERO CRD420251034524).SettingStudies published were identified through EMBASE, ProQuest, Google Scholar, and PubMed.ParticipantsA total of 3967 participants contributed 92,323 training samples. Internal validation included 2331 controls and 2449 VPD cases, generating 81,143 validation samples. Ages ranged from 1 to 93 years.…

Artificial Intelligence Applications in Cleft Lip and Palate Diagnosis, Prediction, and Treatment: A Systematic Review and Meta-Analysis.

ObjectiveCleft lip and cleft palate are common craniofacial abnormalities, causing significant functional, esthetic, and psychosocial issues if not treated early. Artificial intelligence (AI) is increasingly explored in cleft lip and/or palate (CL/P); however, the quality, consistency, and clinical readiness of the available evidence remain unclear. This study systematically reviewed the existing literature on AI applications in CL/P care and performed an exploratory meta-analysis.DesignA comprehensive search was performed on PubMed, WOS, Scopus, and IEEE Xplore until November 2025, following …

The role of artificial intelligence in pre-operative prediction of completeness of cytoreduction for peritoneal surface malignancies: a scoping review.

BACKGROUND: Complete cytoreduction is the most important prognostic factor for patients with peritoneal surface malignancies (PSM) and its prediction remains a clinical challenge. Artificial intelligence (AI) offers a novel opportunity to integrate clinical and imaging features to support surgical decision-making. This scoping review aimed to analyse applications of AI for predicting cytoreduction completeness in PSM. METHODS: A scoping review was conducted in accordance with PRISMA-ScR guidelines and registered with Open Science Framework. PubMed, Scopus, and Embase were searched from 2000 t…

Validation of a Pretrained Artificial Intelligence Model for Pancreatic Cancer Detection on Diagnosis and Prediagnosis Computed Tomography Scans.

PURPOSE: To evaluate PANCANAI, a previously developed AI model for pancreatic cancer (PC) detection, on a longitudinal cohort of patients. In particular, aiming for PC detection on scans acquired before histopathologic diagnosis was assessed. MATERIALS AND METHODS: The model has been previously trained to predict PC suspicion on 2134 portal venous CTs. In this study, the algorithm was evaluated on a retrospective cohort of Danish patients with biopsy-confirmed PC and with CT scans acquired between 2006 and 2016. The sensitivity was measured, and bootstrapping was performed to provide median a

A novel Artificial Intelligence-assisted white light endoscopic model in the diagnosis of cardia atrophy: a multicenter study.

BACKGROUND AND AIMS: Atrophy extends beyond the cardia is open atrophy and closely related to gastric cancer. However, there is difficulty i … r and three junior endoscopists made online diagnoses, comparing the performance differences to the artificial intelligence (AI)-assisted system. RESULTS: In the internal test dataset, the accuracy, sensitivity, and specificity of the AI-assisted cardia atrophy diagnostic system were 0.927, 0.941, and 0.919, respectively, with a positivev predictive value (PPV) of 0.878 …

От прогнозирования к вмешательству: Искусственный интеллект для адаптивного реагирования и моделирования токсичности в клеточной терапии для гематологовых злодеяний.

Гематологическая магнелезность, включая острую лейкемию миэлоида, миэлодипластические синдромы, лимфому и множественную миелому, характеризуется глубокой биологической гетерогенностью и высокодинамичными траекториями лечения, которые традиционные статические прогнозирующие системы неполно улавливают. Клеточная терапия, такая, как химерик антигенная рецепторная терапия Т-клеток и трансплантация стволовых клеток с гематополией, предлагает потенциально лечебные варианты для рецидива или рефракторного заболевания, однако результаты остаются весьма различными, а управленческие решения, касающиеся и

Совпадение в аннотации оригинала
Hematologic malignancies, including acute myeloid leukemia, myelodysplastic syndromes, lymphoma, and multiple myeloma, are characterized by … and toxicity surveillance continue to be largely protocol-driven rather than individually adapted. Artificial intelligence (AI) and machine learning (ML) have demonstrated substantial promise in diagnostic support, prognostic stratification, and multimodal data integration across hematologic malignancies, but existing models remain predominantly static and related to pr …

The role of artificial intelligence in thyroid cytology of indeterminate nodules: from digital cytology to multimodal precision triage.

Indeterminate thyroid cytology is among the most challenging bottlenecks in thyroid nodule management and continues to be a significant source of risk stratification ambiguity and potentially preventable diagnostic surgeries. While molecular analysis has helped refine preoperative risk stratification, especially among Bethesda III (AUS) and Bethesda IV (FN/SFN) thyroid nodules, issues remain regarding positive predictive value, availability, and subsequent malignancy risk, even among those having the "negative" molecular risk assessment. The field of artificial intelligence (AI) is presently e…

Artificial Intelligence Applied to Electrocardiograms Recorded in Sinus Rhythm for Detection and Prediction of Atrial Fibrillation: A Scoping Review.

Background and Objectives: Subclinical paroxysmal atrial fibrillation (AF) is often undetected by conventional screening strategies, until complications emerge. Artificial intelligence (AI) applied to sinus rhythm electrocardiograms has emerged as a promising tool to identify individuals with occult AF and to predict the risk of future incident AF. This scoping review synthesizes evidence from original studies evaluating AI models trained on sinus rhythm ECGs for AF detection or AF prediction. Materials and Methods: A comprehensive search of MEDLINE, Embase, Web of Science, Scopus, and IEEE Xp…

Artificial intelligence for chest imaging in hantavirus pulmonary syndrome: A review of practical considerations for rare-disease imaging.

Hantavirus pulmonary syndrome (HPS) is an uncommon zoonotic respiratory illness with a high case fatality rate. Recent travel-associated Andes orthohantavirus clusters have renewed interest in early radiographic recognition of the disease outside its usual geographic range. Artificial intelligence (AI) tools developed during the COVID-19 pandemic now inform several radiology workflows, but the application of AI to HPS chest imaging remains largely unexplored. This narrative review summarises the imaging features of HPS across modalities, considers lessons from AI applications in COVID-19 and v…

Artificial intelligence for pathologic myopia classification based on the META-PM system: a systematic review and meta-analysis.

BACKGROUND: Artificial intelligence (AI) has shown considerable potential for pathologic myopia (PM) detection, yet its overall diagnostic performance under the META-PM classification framework remains uncertain. METHODS: A comprehensive literature search was conducted across PubMed, Web of Science, IEEE Xplore, and Embase up to February 10, 2026. Studies applying deep learning models for PM classification using the META-PM system were included. Pooled sensitivity, specificity, and hierarchical summary receiver operating characteristic (HSROC) analyses were calculated. Twelve studies were eli…

Artificial Intelligence as a Catalyst for Value-Based Health Insurance in the United States: Narrative Review and Policy Perspective.

The United States health insurance system is at a critical crossroads. Inflating costs, fragmented care, and administrative inefficiencies have revealed the limitations of the Fee-for-Service (FFS) model. This long-standing structure, while once effective in expanding access, now struggles to deliver efficiency and value. Value-based care (VBC) aims to realign incentives toward outcomes, quality, and efficiency. This article explores how artificial intelligence (AI) can serve as the digital backbone to accelerate the transition from FFS to VBC. The article reviews evidence from bundled payment…

Hospital Artificial Intelligence Tools and Inpatient Utilization and Costs in Older Adults with Alzheimer's Disease and Related Dementias.

BACKGROUND: Hospitals are increasingly adopting artificial intelligence and machine learning (AI/ML) tools to support clinical decision making and care management. However, evidence on how hospital AI/ML adoption relates to inpatient utilization and spending among clinically complex populations remains limited. Older adults with Alzheimer's disease and related dementias (ADRD) experience higher rates of readmissions and potentially avoidable hospitalizations. METHODS: Cross-sectional study was conducted using 2023 inpatient claims linked to the Medicare Beneficiary Summary File and the Americ…

Microbial dysbiosis and wound healing in diabetic foot ulcers: a mini review with a note on the role of artificial intelligence.

Diabetic foot ulcers (DFUs) are a serious diabetes-related complication characterized by high rates of amputation and mortality. Emerging ev … Future perspectives point towards personalized microbial medicine, integrating multi-omics data and artificial intelligence to match interventions with specific microbial ecotypes, which may reduce the global burden of DFUs.

Suicide and self-harm in the age of generative artificial intelligence: The case of ChatGPT and rise of suicide-related lawsuits.

Self-harm and suicide trends have taken a new turn in the era of GenAI and communicative chatbots. Recent OpenAI's own report suggests that 1.2 million weekly ChatGPT users appear to be expressing suicidal thoughts, and 80,000 users are potentially experiencing mania and psychosis. At the same time, OpenAI and other AI companies are facing lawsuits in several countries alleging that their chatbots encouraged vulnerable individuals to harm themselves. These lawsuits have sparked a growing scholarly debate about responsibility, safety, and the ethical use of chatbots in mental health services. G

Exploring the application of Artificial Intelligence in palliative care and its practical, technical and ethical considerations: a scoping review.

BACKGROUND: Palliative care improves the quality of life of people living with life-limiting conditions and their families; however, global access remains constrained by workforce shortages and late referrals. Artificial Intelligence (AI) has been proposed as a scalable solution for optimising the identification of needs, supporting clinical decision-making, and enhancing care delivery. However, real-world evidence of the application of AI in palliative care remains sparse, particularly regarding its impact on quality of life, quality of care, and associated practical, technical and ethical ch…

Diagnostic Accuracy of Artificial Intelligence-Based Electrocardiography for the Detection of Heart Diseases: A Systematic Review and Meta-Analysis.

Background/Objectives: Electrocardiography augmented by artificial intelligence (AI-ECG) has been put forward as an inexpensive, scalable means of identifying a wide range of cardiac disorders, but reported performance differs markedly with the condition targeted, the algorithm, and the reference standard. Our pre-specified primary objective was to estimate the diagnostic accuracy of AI-ECG for heart failure/left ventricular systolic dysfunction (HF/LVSD); accuracy in other cardiac conditions was examined condition by condition, and a cross-condition estimate was computed only as a secondary, …

Impact of Artificial Intelligence Assistance on Diagnosing Traumatic Pneumothorax: A Comparison of Specialist and Non-Specialist Emergency Physicians.

INTRODUCTION: Supine chest radiography is routinely used in trauma care; however, its sensitivity is limited in pneumothorax detection. Although artificial intelligence (AI) has recently been introduced as a diagnostic support tool for chest radiograph interpretation, its use in trauma radiographs and its interaction with physician experience remain unclear. We aimed to evaluate the diagnostic performance of AI-assisted image interpretation in traumatic pneumothorax detection among emergency medicine specialists and non-specialists. METHODS: In this retrospective single-center study, 34 supin…