Domestic Violence

An overview of diagnostics and therapeutics using large language models.

There is an acute need for solutions to treat stress and trauma-related sequelae, and there are well-documented shortages of qualified human professionals. Artificial intelligence (AI) presents an opportunity to create advanced screening, diagnosis, and treatment solutions that relieve the burden on people and can provide just-in-time interventions. Large language models (LLMs), in particular, are...

Machine learning models predict triage levels, massive transfusion protocol activation, and mortality in trauma utilizing patients hemodynamics on admission.

BACKGROUND: The effective management of trauma patients necessitates efficient triaging, timely activation of Massive Blood Transfusion Protocols (MTP), and accurate prediction of in-hospital outcomes. Machine learning (ML) algorithms have emerged as up-and-coming tools in the domains of optimizing triage decisions, improving intervention strategies, and predicting clinical outcomes, consistently ...

Perceptions and detection of AI use in manuscript preparation for academic journals.

The rapid advances in Generative AI tools have produced both excitement and worry about how AI will impact academic writing. However, little is known ...

Discovering transformation products of pharmaceuticals in domestic wastewaters and receiving rivers by using non-target screening and machine learning approaches.

Wastewater treatment plants (WWTPs) are an important source of pharmaceuticals in surface water, but information about their transformation products (...

AI as a Medical Device Adverse Event Reporting in Regulatory Databases: Protocol for a Systematic Review.

BACKGROUND: The reporting of adverse events (AEs) relating to medical devices is a long-standing area of concern, with suboptimal reporting due to a r...

Developing a deep learning model for predicting ovarian cancer in Ovarian-Adnexal Reporting and Data System Ultrasound (O-RADS US) Category 4 lesions: A multicenter study.

PURPOSE: To develop a deep learning (DL) model for differentiating between benign and malignant ovarian tumors of Ovarian-Adnexal Reporting and Data S...

ChatGPT and assistive AI in structured radiology reporting: A systematic review.

INTRODUCTION: The rise of transformer-based large language models (LLMs), such as ChatGPT, has captured global attention with recent advancements in a...

Simplifying risk stratification for thyroid nodules on ultrasound: validation and performance of an artificial intelligence thyroid imaging reporting and data system.

PURPOSE: To validate the performance of a recently created risk stratification system (RSS) for thyroid nodules on ultrasound, the Artificial Intellig...

AI-based selection of individuals for supplemental MRI in population-based breast cancer screening: the randomized ScreenTrustMRI trial.

Screening mammography reduces breast cancer mortality, but studies analyzing interval cancers diagnosed after negative screens have shown that many ca...

The theranostic performance of Chat-GPT against urological trauma.

Non-invasive screening of bladder cancer using digital microfluidics and FLIM technology combined with deep learning.

Non-invasive screening for bladder cancer is crucial for treatment and postoperative follow-up. This study combines digital microfluidics (DMF) techno...

Comparing machine learning screening approaches using clinical data and cytokine profiles for COVID-19 in resource-limited and resource-abundant settings.

Accurate screening of COVID-19 infection status for symptomatic patients is a critical public health task. Although molecular and antigen tests now ex...

Clinical evaluation of an artificial intelligence-assisted cytological system among screening strategies for a cervical cancer high-risk population.

BACKGROUND: Primary cervical cancer screening and treating precancerous lesions are effective ways to prevent cervical cancer. However, the coverage r...

A Support Vector Machine-Assisted Metabolomics Approach for Non-Targeted Screening of Multi-Class Pesticides and Veterinary Drugs in Maize.

The contamination risks of plant-derived foods due to the co-existence of pesticides and veterinary drugs (P&VDs) have not been fully understood. With...

Prediction of Robotic Anastomosis Competency Evaluation (RACE) metrics during vesico-urethral anastomosis using electroencephalography, eye-tracking, and machine learning.

Residents learn the vesico-urethral anastomosis (VUA), a key step in robot-assisted radical prostatectomy (RARP), early in their training. VUA assessm...

Prediction of mortality among severely injured trauma patients A comparison between TRISS and machine learning-based predictive models.

BACKGROUND: Given the huge impact of trauma on hospital systems around the world, several attempts have been made to develop predictive models for the...

Quality of science journalism in the age of Artificial Intelligence explored with a mixed methodology.

Science journalists, traditionally, play a key role in delivering science information to a wider audience. However, changes in the media ecosystem and...

Systematic review of machine learning models in predicting the risk of bleed/grade of esophageal varices in patients with liver cirrhosis: A comprehensive methodological analysis.

Esophageal varices (EV) in liver cirrhosis carry high mortality risks. Traditional endoscopy, which is costly and subjective, prompts a shift towards ...

Tackling the small data problem in medical image classification with artificial intelligence: a systematic review.

Though medical imaging has seen a growing interest in AI research, training models require a large amount of data. In this domain, there are limited s...

Assessing the effectiveness of artificial intelligence (AI) in prioritising CT head interpretation: study protocol for a stepped-wedge cluster randomised trial (ACCEPT-AI).

INTRODUCTION: Diagnostic imaging is vital in emergency departments (EDs). Accessibility and reporting impacts ED workflow and patient care. With radio...