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Domestic Violence

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AI implementation: Radiologists' perspectives on AI-enabled opportunistic CT screening.

OBJECTIVE: AI adoption requires perceived value by end-users. AI-enabled opportunistic CT screening ...

Deep learning Radiomics Based on Two-Dimensional Ultrasound for Predicting the Efficacy of Neoadjuvant Chemotherapy in Breast Cancer.

We investigate the predictive value of a comprehensive model based on preoperative ultrasound radiom...

Evaluation of AI-enhanced non-mydriatic fundus photography for diabetic retinopathy screening.

OBJECTIVE: To assess the feasibility of using non-mydriatic fundus photography in conjunction with a...

Houston, We Have AI Problem! Quality Issues with Neuroimaging-Based Artificial Intelligence in Parkinson's Disease: A Systematic Review.

In recent years, many neuroimaging studies have applied artificial intelligence (AI) to facilitate e...

Integrating Laser-Induced Breakdown Spectroscopy and Ensemble Learning as Minimally Invasive Optical Screening for Diabetes.

Diabetes mellitus is a prevalent chronic disease necessitating timely identification for effective m...

Common Critiques and Recommendations for Studies in Neurology Using Machine Learning Methods.

Machine learning (ML) methods are becoming more prevalent in the neurology literature as alternative...

An artificial intelligence accelerated virtual screening platform for drug discovery.

Structure-based virtual screening is a key tool in early drug discovery, with growing interest in th...

Empowering Portable Age-Related Macular Degeneration Screening: Evaluation of a Deep Learning Algorithm for a Smartphone Fundus Camera.

OBJECTIVES: Despite global research on early detection of age-related macular degeneration (AMD), no...

Promoting smartphone-based keratitis screening using meta-learning: A multicenter study.

OBJECTIVE: Keratitis is the primary cause of corneal blindness worldwide. Prompt identification and ...

Artificial intelligence assisted automatic screening of opportunistic osteoporosis in computed tomography images from different scanners.

OBJECTIVES: It is feasible to evaluate bone mineral density (BMD) and detect osteoporosis through an...

Innovative virtual screening of PD-L1 inhibitors: the synergy of molecular similarity, neural networks and GNINA docking.

Immune checkpoint inhibitors targeting PD-L1 are crucial in cancer research for preventing cancer c...

Cost-Effectiveness of AI for Risk-Stratified Breast Cancer Screening.

IMPORTANCE: Previous research has shown good discrimination of short-term risk using an artificial i...

Artificial intelligence guided screening for cardiomyopathies in an obstetric population: a pragmatic randomized clinical trial.

Nigeria has the highest reported incidence of peripartum cardiomyopathy worldwide. This open-label, ...

Exploiting Metal-Organic Frameworks for Vinylidene Fluoride Adsorption: From Force Field Development, Computational Screening to Machine Learning.

Metal-organic frameworks (MOFs) represent a distinctive class of nanoporous materials with considera...

Can large language models be new supportive tools in coronary computed tomography angiography reporting?

The advent of large language models (LLMs) marks a transformative leap in natural language processin...

Comparison of AI-integrated pathways with human-AI interaction in population mammographic screening for breast cancer.

Artificial intelligence (AI) readers of mammograms compare favourably to individual radiologists in ...

Application of artificial intelligence in lung cancer screening: A real-world study in a Chinese physical examination population.

BACKGROUND: With the rapid increase of chest computed tomography (CT) images, the workload faced by ...

Developing Machine Vision in Tree-Fruit Applications-Fruit Count, Fruit Size and Branch Avoidance in Automated Harvesting.

Recent developments in affordable depth imaging hardware and the use of 2D Convolutional Neural Netw...

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