Identifying and Reporting Dependent Adult abuse

A scalable EEG-based spatial neglect detection system in augmented reality for stroke patients.

BACKGROUND: Spatial neglect is a common visuospatial attention disorder following a stroke. To overcome weaknesses associated with classic pen-and-paper tests used in some clinical settings, we developed AREEN: an AR-guided EEG-based Neglect detection system. AREEN previously demonstrated that the EEG activity of patients with neglect was distinguishable from that of patients without neglect. Howe...

Jo-SNC: Combating Noisy Labels Through Fostering Self- and Neighbor-Consistency.

Label noise is pervasive in various real-world scenarios, posing challenges in supervised deep learning. Deep networks are vulnerable to such label-corrupted samples due to the memorization effect. One major stream of previous methods concentrates on identifying clean data for training. However, these methods often neglect imbalances in label noise across different mini-batches and devote insuffic...

A Core Outcome Set for Intact Abdominal Aortic Aneurysms Under Surveillance.

BACKGROUND: Current literature on AAA is characterized by selective outcome reporting, while guideline recommendations are frequently based on studies...

Artificial intelligence in intensive care units: a scoping review addressing the translational gap to clinical practice.

BACKGROUND: Critically ill patients generate large volumes of complex data, creating challenges for timely clinical decision making in intensive care ...

Smartphone-based digital phenotyping for detection of high-risk depression and anxiety in Korean community settings.

BACKGROUND: Smartphones generate continuous behavioral signals such as mobility and activity patterns, offering scalable opportunities for monitoring ...

Review of agentic artificial intelligence (AI) in radiology: from current clinical integration to future innovations.

AIM: Artificial intelligence (AI) is one of the most revolutionary developments in the field of medicine in recent history, with radiology being one o...

Recent advances in machine learning-enhanced extracellular vesicle omics for oncology.

Extracellular vesicles (EVs) are nanoscale, membrane-bound particles that carry nucleic acids, proteins, metabolites, and lipids. Their omics profiles...

Mass Media Narratives of Psychiatric Adverse Events Associated With Generative AI Chatbots: Rapid Scoping Review.

BACKGROUND: Generative artificial intelligence (AI) chatbots have rapidly entered public use, including in contexts involving emotional support and me...

Domain specific multimodal large language model for automated endoscopy reporting with multicenter prospective validation.

Accurate endoscopy reports are crucial for the diagnosis and management of patients with upper gastrointestinal (UGI) diseases, yet errors and omissio...

Measuring the Impact of AI on Report-Drafting Efficiency in Chest Computed Tomography Interpretation: Retrospective Analysis.

BACKGROUND: Artificial intelligence (AI), particularly deep learning, has shown promise in enhancing medical image interpretation and improving radiol...

A comprehensive analysis of brain network complexity in task-based fMRI using entropy: systematic review.

Entropy-based analysis is increasingly used in task-based functional magnetic resonance imaging (fMRI) to quantify neural signal complexity and inform...

Technical Description of the Mini Far-Lateral Approach: A Refined, Stability-Preserving Corridor to the Petroclival Region.

BACKGROUND AND OBJECTIVES: The far-lateral approach remains essential for accessing ventral and ventrolateral lesions of the craniovertebral junction....

Rethinking diagnostic performance metrics in imaging AI: lessons from caries detection on radiographs.

Artificial intelligence (AI) systems for radiographic caries detection are commonly evaluated using a small set of performance metrics, yet these meas...

Machine Learning Models Used to Predict Abdominal Aortic Aneurysm Growth and Rupture: A Systematic Review and Critical Appraisal.

BACKGROUND: Abdominal aortic aneurysm (AAA) rupture remains a major cause of mortality, and diameter-based surveillance is an imperfect predictor of r...

Breast Arterial Calcification on Mammography and Cardiovascular Outcomes in Women: A Meta-analysis.

Breast arterial calcification (BAC) is commonly observed on screening mammography and may provide a low-cost opportunistic marker to enhance cardiovas...

Multimodal AI for Alzheimer Disease Diagnosis: Systematic Review of Datasets, Models, and Modalities.

BACKGROUND: Early detection of Alzheimer disease (AD) is essential for timely intervention; yet, diagnostic performance varies widely across modalitie...

Whole-body magnetic resonance imaging for cancer screening in asymptomatic adults: a multicenter study.

OBJECTIVES: Whole-body MRI is increasingly used for preventive health screening; however, the prevalence and distribution of incidental oncologically ...

Multi-output LSTM-based prediction of postoperative delirium: integrating baseline and perioperative data for enhanced risk stratification in older spine surgery patients.

INTRODUCTION: Postoperative delirium (POD) adversely affects clinical outcomes among older adults undergoing spine surgery. However, existing predicti...

Contemporary clinical incident analysis methods used within acute care settings: a scoping review.

OBJECTIVE: The objective of this review was to explore and synthesize the research on the use of contemporary incident analysis methods in acute care ...

Artificial intelligence and radiomics in bladder cancer MRI: a scoping review of applications, performance, and barriers to clinical translation.

Artificial intelligence (AI) and radiomics show significant potential to augment bladder cancer (BC) MRI but face a critical translational gap. This s...