Domestic Violence

Development and proof-of-concept of a treatment target recommendation algorithm in the context of cognitive processing therapy.

Background: Cognitive Processing Therapy (CPT) is an effective, widely supported treatment for PTSD, but patient response varies considerably. Optimally targeting maladaptive trauma-related beliefs (stuck points) may significantly enhance treatment outcomes. This study evaluated the feasibility of developing a recommendation algorithm that helps clinicians identify specific patient-endorsed stuck ...

No Normal Brain: How Demographic Exclusion Undermines Neuroimaging AI Validity.

BACKGROUND AND OBJECTIVE: Neuroimaging AI systems increasingly influence clinical decisions, yet demographic exclusions in training datasets may compromise their scientific validity and clinical safety. This analysis examines how demographic concentration in major neuroimaging repositories undermines the fundamental neurobiological principle that there is no single "normal" brain, potentially crea...

Standardizing case definitions for hoof lesions and lameness: A scoping review to improve machine learning applications in dairy cattle.

Lameness in dairy cattle, primarily caused by hoof lesions, remains a widespread issue in North America with significant welfare, economic, and sustai...

Co-Designed Mental Health Screening App (Here for You) for University Students: Pilot Feasibility Mixed Methods Study.

BACKGROUND: Mental health disorders are a growing public health concern among university students globally and in India, exacerbated by stigma and lim...

Defining operational safety in clinical artificial intelligence systems.

The clinical adoption of artificial intelligence (AI) has focused on enabling automation, but conventional accuracy metrics fail to answer a key quest...

Artificial intelligence-enhanced microsurgical training: a systematic review.

Artificial intelligence (AI) offers objective, adaptive tools for skill enhancement in microsurgical training, but evidence is fragmented. This system...

Assessing the Reliability of Large Language Models for Evaluation of Risk of Bias in Randomized Clinical Trials.

OBJECTIVE: Systematic reviews depend on rigorous risk-of-bias (RoB) assessments to ensure credibility, yet manual evaluation using the Cochrane RoB 2 ...

Non-invasive screening for ovarian cancer by combining serum SERS with interpretable machine learning models.

Early identification of malignant ovarian tumors is critical for informing treatment decisions and enhancing patients' quality of life. As the third m...

AI-driven CRISPR screening: optimizing gene editing through automation and intelligent decision support.

BACKGROUND: CRISPR-based genetic screening has become a central methodology in functional genomics, enabling systematic interrogation of gene function...

Predicting Surgical Outcomes in Breast Reconstruction With Machine Learning: A Systematic Review.

INTRODUCTION: The applications of artificial intelligence (AI) in plastic surgery have grown considerably in recent years. As large patient datasets b...

Machine Learning for Predicting Stroke Risk Stratification Using Multiomics Data: Systematic Review.

BACKGROUND: Stroke is a complex, multidimensional disorder influenced by interacting inflammatory, immune, coagulation, endothelial, and metabolic pat...

Screening for Clinically Significant Nephrolithiasis Based on Simple Health Checkup Clinical and Urine Parameters in General Populations: Multicenter Machine Learning Study.

BACKGROUND: Nephrolithiasis affects approximately 15% of the population and often remains undetected in asymptomatic individuals. Current diagnostic a...

Analysis of Associated Factors and Construction of Risk Prediction Models for Frailty in Hospitalized Older Adults Living With HIV: Protocol for a Prospective Observational Study.

BACKGROUND: The aging trend of people living with HIV or AIDS in China is increasing day by day. Frailty is a common condition among older adults livi...

Automated Report Generation in Ophthalmology: Integrating Artificial Intelligence, Multimodal Imaging, and Clinical Data.

Artificial intelligence (AI) has emerged as a transformative force in ophthalmology, enabling automated, accurate, and efficient clinical reporting. T...

An Artificial Intelligence-Selected Multifunctional Oligopeptide Coated Biphasic Calcium Phosphate (BCP) Scaffold Promotes Bone Defect Repair.

Bone defects caused by inflammation, trauma, tumor resection, or tooth extraction present persistent clinical challenges, primarily because of the lim...

Landmark-based deep learning for radiographic screening for developmental dysplasia of the hip in infants: Development and external evaluation with IHDI-guided triage.

BACKGROUND: In Japan, secondary screening for developmental hip dysplasia has expanded. However, the capacity of screening programs has outpaced the a...

Artificial Intelligence for radiation dose reduction in computed tomography: a narrative synthesis of clinical evidence from 2020 to 2025.

Computed tomography (CT) is essential to modern clinical practice but contributes substantially to population radiation exposure, particularly in onco...

Comparison of Artificial Intelligence Chatbots and Dental Students on Context of Dental Trauma.

AIM: Daily use of chatbots has become widespread in dental education just as in every other field. Dental students consult them when performing tasks ...

A framework for enhancing pharmaceutical integrity and patient safety: novel mobile health solution integrating smart packaging and computer vision.

Counterfeit and substandard pharmaceuticals represent a critical global health crisis, with the World Health Organisation (WHO) reporting that falsifi...

Exploration of an interpretable machine learning-based screening manner for low muscle mass among Chinese community-dwelling older adults using routine physical examination information.

BACKGROUND: With the accelerating aging of the global population, muscle health issue occurs commonly as an age-related process in older people. The c...