Emergency Medicine

Training the diagnostic artificial intelligence in thyroid sonography: how well is deep learning truly learning?

INTRODUCTION: The use of artificial intelligence (AI) for TI-RADS classification in neck sonography for the assessment of thyroid nodules has been proven beneficial. We evaluated the learning curve of such AI in a real-world setting. METHODS: Between 03/2023 and 06/2024, 110 patients with 176 thyroid nodules were examined and classified according to ACR TI-RADS classification using 3D-ultrasound P...

Surgical Robotic System for Precision Femoral Fracture Reduction.

Malalignment after femoral fracture repair remains common, with up to one-third of patients experiencing malrotations. Manual femoral fracture reduction remains physically demanding and fluoroscopy-dependent. Surgeons must apply traction forces to overcome forces generated by the surrounding muscles during the reduction process. Current orthopaedic robots, designed primarily for arthroplasty or sp...

Computerized Self-Reported Medical History Taking to Support Early Rule Out of Major Adverse Cardiac Events in Patients With Acute Chest Pain: Post Hoc Analysis of the CLEOS-CPDS Prospective Cohort Study.

BACKGROUND: Self-reported, computerized history taking (CHT) may enable efficient collection of medical histories for acute chest pain management. OBJ...

The human metabolome and machine learning improves predictions of the post-mortem interval.

An accurate prediction of the time since death, known as the post-mortem interval, remains a critical research question in forensic and police investi...

Deep learning-based detection of retinal detachment with vitreous hemorrhage in ocular ultrasound images.

Retinal detachment (RD) is a serious ocular disease that can lead to permanent vision loss. In cases with fundus-obscuring vitreous hemorrhage (VH), i...

Acute biological age as a determinant of adverse outcomes requiring hospitalization in Danish emergency department patients.

BACKGROUND: Accurate health assessments in the Emergency Department are critical for guiding treatment decisions. However, these assessments are often...

Characterization of acoustic emission parameters and identification of staged fracture propagation in solidified body-coal combination based on experimental and machine learning approaches.

Exploring the toxicological mechanisms of Benzo[a]anthracene (BaA) exposure in lung adenocarcinoma (LUAD) via network toxicology, machine learning, and multi-dimensional bioinformatics analysis.

BACKGROUND: Lung adenocarcinoma (LUAD) is a major lung cancer subtype influenced by environmental factors. Benzo[a]anthracene (BaA), a common Group 2B...

Artificial intelligence-derived transition zone PSA density as a triage tool to reduce unnecessary prostate systematic biopsies in MRI-negative men.

OBJECTIVES: The study aimed to assess the predictive performance of transition zone PSA density (TZ-PSAD) compared to conventional PSA density (PSAD) ...

Smartphone-Based Portable Slit Lamp in Anterior Segment Diseases: A Narrative Review of Clinical Assessment and Integration with Artificial Intelligence.

Smartphone-based portable slit lamps are rapidly evolving from simple add-ons into practical, low-cost front-line tools for anterior segment care beyo...

Integrative network toxicology and experimental evidence reveal mechanisms underlying diethyl phthalate-induced initiation and progression of endometrial cancer.

Diethyl phthalate (DEP) is a ubiquitous environmental endocrine-disrupting chemical (EDC). Epidemiological studies have suggested a potential associat...

Elucidating the toxicological impact and mechanism of plasticizers exposure on Alzheimer's disease through network toxicology and molecular docking.

This study aimed to explore the underlying mechanisms and key targets of widely used plasticizers, including dimethyl phthalate (DMP), diethyl phthala...

Machine learning in forensic toxicology: Concepts, applications and challenges in bioanalysis, ADME, and toxicodynamics.

Forensic toxicology focuses on the detection, quantification, and interpretation of medicinal and recreational drugs, other chemicals or poisons, and ...

Artificial intelligence in trauma care: applications, ethical challenges, and pathways toward responsible integration.

PURPOSE OF REVIEW: Artificial intelligence is increasingly applied across the trauma care continuum, from prehospital triage to in-hospital decision-m...

Ambient Artificial Intelligence Scribe Adoption and Documentation Time in the Emergency Department.

STUDY OBJECTIVES: To describe real-world adoption of an ambient artificial intelligence (AI) scribe in the emergency department (ED) and compare docum...

Environmental bisphenols hijack the Hmox1 and Cdh1 to trigger premature ovarian insufficiency: A multi-omics investigation.

BACKGROUND: Bisphenols A (BPA), bisphenols F (BPF), and bisphenols S (BPS) are environmental endocrine disruptors linked to premature ovarian insuffic...

NIAID Biodosimetry Strategic Plan.

In the face of emerging threats from natural disasters, nuclear accidents, and potential malicious use of radiation, the National Institute of Allergy...

Label-Free 3D Holotomography and AI Quantification of Macrophage Inflammation Induced by Urban Particulate Matter.

OBJECTIVES: Particulate matter (PM) is well established as an environmental hazard linked to an increased risk of disease. Although numerous studies h...

Machine Learning Algorithm to Predict Change in the Decision-Making for Thoracolumbar Fractures Without Neurological Deficit After MRI: A Multicenter Study.

Study DesignA multicenter study.ObjectiveTo develop a machine learning algorithm to predict when magnetic resonance imaging (MRI) may change the thora...

Enhancing Surgeons' Cognitive Performance in Colorectal Surgery: A Narrative Review.

BACKGROUND: Colorectal surgery continues to exhibit variability in outcomes despite advancements in minimally invasive and robotic techniques. Increas...