Identifying and Reporting Dependent Adult abuse

World Health Organization classification of tumours of the breast 6th edition 2026.

The 6th edition of the WHO Classification of Breast Tumours introduces both major and minor changes based on recent advances in our understanding of breast biology, developments in diagnostic modalities, identification of specific molecular targets and new treatment regimens necessitating modifications to pathology reporting and tumour biomarker categorisation. This review summarises the main chan...

Fall Detection Based on Computer Vision: A Systematic Mapping Study.

Falls are a leading cause of injury and mortality among older adults, motivating growing interest in video-based computer vision (CV) fall detection systems. This study presents a systematic mapping of vision-based fall detection in video, synthesizing evidence from 433 primary studies published through 2025 and retrieved from five databases using explicit eligibility criteria and independent dual...

Use of AI to Predict and Support Medication Adherence in Patients With Breast Cancer: Systematic Review.

BACKGROUND: Oral medications are commonly used in the treatment of breast cancer (BC), despite high rates of nonadherence. As adherence is fundamental...

Reporting efficiency in diagnostic imaging: Can plug-and-play general-purpose large language models outperform conventional speech recognition?

OBJECTIVES: To compare conventional speech recognition (CSR) and a general-purpose large language model (LLM) in radiology reports, focusing on genera...

Oil spill detection on sea surface with dual-polarimetric SAR imagery integrating polarization features and oil-seawater boundary information.

Oil Spill can cause a series of ecological disasters and irreversible damages to marine environment, making the timely detection of oil films on the s...

Spectral-Spatial-Temporal Kolmogorov-Arnold Network for Hyperspectral Change Detection.

Hyperspectral change detection (HCD) aims to recognize altered areas between hyperspectral images (HSIs) captured at different times, which is one of ...

Cuproptosis-related circulating non-coding RNAs as diagnostic and prognostic biomarkers in oncology.

Cuproptosis is a recently described copper-dependent form of regulated cell death linked to mitochondrial metabolic stress and is emerging as a biolog...

Towards interpretable AI in personalized medicine through a radiological-biological radiomics dictionary linking semantic Lung-RADS and imaging radiomics features.

BACKGROUND: Lung cancer remains the leading cause of cancer-related mortality worldwide, with survival largely dependent on early detection. Standard-...

The predictive value of serological markers for successful weaning and 30-day mortality in patients with severe intracerebral hemorrhage.

AIM: This study intends to screen serological indicators related to weaning outcomes and 30-day mortality in severe intracerebral hemorrhage (ICH) pat...

Commercial AI Model Diagnostic Accuracy for Intracranial Large- and Medium-Vessel Occlusion in Emergency CT Angiography.

The diagnostic accuracy of AIDOC-VO, the first commercial artificial intelligence tool for intracranial large-and medium-vessel occlusion (LVO/MeVO) d...

AI triage of duodenal biopsies improves workflow.

AIMS: To develop, deploy and evaluate artificial intelligence (AI) for triaging duodenal biopsies within a National Health Service (NHS) histopatholog...

AI Methods for Implementation Science (AIM-IS): developing a framework, toolkit, and reporting standard for the responsible use of AI in implementation practice and research.

BACKGROUND: Artificial intelligence (AI), including machine learning, natural language processing, and large language models, may support implementati...

Minimum joint space width demonstrates higher inter-and intra-observer reliability than Kellgren-Lawrence grading in knee osteoarthritis.

PURPOSE: The purpose of this systematic review was to compare the inter- and intra-observer reliability of Kellgren-Lawrence (KL) grading versus minim...

Predicting Nosocomial Infections in Hematologic Patients: A Machine Learning Model Based on Dynamic Body Temperature Trajectories.

AIMS: To identify body temperature dynamic patterns and develop a machine learning model for the early detection of nosocomial infections. DESIGN: A r...

Hypotension Prediction Index-Guided Hemodynamic Management on Postoperative Organ Outcome: A Systematic Review and Meta-Analysis of Randomized Clinical Trials.

Intraoperative hypotension (IOH) is a frequent occurrence during noncardiac surgery. Hypotensive episodes can compromise tissue perfusion, and cumulat...

Development and Validation of a Web Calculator for Predicting the Risk of Lower Limb Varicose Veins.

The aims of the present study were to develop and validate a predictive model for lower limb Varicose Veins, and to visualize the results using a web ...

Diagnostic accuracy and deployment readiness of AI for burn depth assessment across imaging modalities: a PRISMA-DTA systematic review and meta-analysis.

BACKGROUND: AI-based burn depth assessment is rapidly emerging, yet evidence for diagnostic accuracy, generalizability, and deployment readiness remai...

DPA-Net: A dual-path attention neural network for estimating glycemic metrics from self-monitored blood glucose data.

Continuous glucose monitoring (CGM) provides dense and dynamic glucose profiles that enable reliable estimation of glycemic metrics, such as time-abov...

Automated scout-image-based estimation of contrast agent dosing: a deep learning approach.

BACKGROUND: Optimal contrast agent dosing in computed tomography (CT) depends on accurate patient weight, yet manual measurements increase workload an...

Diagnostic accuracy of artificial intelligence-assisted infant hip ultrasound interpretation for developmental dysplasia of the hip: systematic review and meta-analysis.

BACKGROUND: Ultrasound is the standard imaging test for infant developmental dysplasia of the hip (DDH) but is highly operator-dependent, leading to v...