Domestic Violence

Future of service member monitoring: the intersection of biology, wearables and artificial intelligence.

While substantial investment has been made in the early identification of mental and behavioural health disorders in service members, rates of depression, substance abuse and suicidality continue to climb. Objective and persistent measures are needed for early identification and treatment of these rising health issues. Considerable potential lies at the intersection of biology, wearables and artif...

Artificial intelligence in paediatric head trauma: enhancing diagnostic accuracy for skull fractures and brain haemorrhages.

Pediatric head trauma is a significant cause of morbidity and mortality, with children, particularly those under two years old, being more susceptible to skull fractures due to their unique physiological and developmental characteristics. A recent study by Azusa Ono et al. examined the impact of repeated imaging in children under 24 months with minor head trauma, revealing that 40.6% of those who ...

The potential benefit of artificial intelligence regarding clinical decision-making in the treatment of wrist trauma patients.

PURPOSE: The implementation of artificial intelligence (AI) in health care is gaining popularity. Many publications describe powerful AI-enabled algor...

Deep Learning-Based Denoising Enables High-Quality, Fully Diagnostic Neuroradiological Trauma CT at 25% Radiation Dose.

RATIONALE AND OBJECTIVES: Traumatic neuroradiological emergencies necessitate rapid and accurate diagnosis, often relying on computed tomography (CT)....

The Potential Clinical Utility of an Artificial Intelligence Model for Identification of Vertebral Compression Fractures in Chest Radiographs.

PURPOSE: To assess the ability of the Annalise Enterprise CXR Triage Trauma (Annalise AI Pty Ltd, Sydney, NSW, Australia) artificial intelligence mode...

Advancements in opportunistic intracranial aneurysm screening: The impact of a deep learning algorithm on radiologists' analysis of T2-weighted cranial MRI.

(1) Background: Unruptured Intracranial Aneurysms (UIAs) are common blood vessel malformations, occurring in up to 3 % of healthy adults. Magnetic Res...

Benchmarking Human-AI collaboration for common evidence appraisal tools.

BACKGROUND AND OBJECTIVE: It is unknown whether large language models (LLMs) may facilitate time- and resource-intensive text-related processes in evi...

Assessing the Reporting Quality of Machine Learning Algorithms in Head and Neck Oncology.

OBJECTIVE: This study aimed to assess reporting quality of machine learning (ML) algorithms in the head and neck oncology literature using the TRIPOD-...

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 radiomics, deep learning, and clinical features for path...

Evaluating text and visual diagnostic capabilities of large language models on questions related to the Breast Imaging Reporting and Data System Atlas 5 edition.

PURPOSE: This study aimed to evaluate the performance of large language models (LLMs) and multimodal LLMs in interpreting the Breast Imaging Reporting...

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 existing challenges in Parkinson's disease (PD) dia...

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 alternatives to traditional statistical methods to address ch...

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 the screening of multi-billion chemical compound lib...

Automated Association for Osteosynthesis Foundation and Orthopedic Trauma Association classification of pelvic fractures on pelvic radiographs using deep learning.

High-energy impacts, like vehicle crashes or falls, can lead to pelvic ring injuries. Rapid diagnosis and treatment are crucial due to the risks of se...

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 processing, offering unprecedented potential in radiology, ...

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 detecting breast cancer. However, AI readers canno...

Detecting pediatric appendicular fractures using artificial intelligence.

OBJECTIVE: The primary objective was to assess the diagnostic accuracy of a deep learning-based artificial intelligence model for the detection of acu...

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 Networks (CNN) in object detection and segmentation ha...

A neural network approach to predict opioid misuse among previously hospitalized patients using electronic health records.

Can Electronic Health Records (EHR) predict opioid misuse in general patient populations? This research trained three backpropagation neural networks ...

Enhancing cervical cancer cytology screening via artificial intelligence innovation.

A double-check process helps prevent errors and ensures quality control. However, it may lead to decreased personal accountability, reduced effort, an...