Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 71,371 to 71,380 of 234,892 articles

Beyond self-reports after anterior cruciate ligament injury - machine learning methods for classifying and identifying movement patterns related to fear of re-injury.

Journal of sports sciences
Anterior cruciate ligament (ACL) tears are prevalent career-ending sports injuries. A barrier to successful return to activity is fear of re-injury. Evaluating psychological readiness is however limited to insufficient self-reported assessments. We d... read more 

Tracking the Debate: Geo-Temporal Sentiment Analysis of Community Water Fluoridation on 'X' (Formerly Twitter) With Five-Year Forecast.

Community dentistry and oral epidemiology
OBJECTIVES: This study examined country-level geo-temporal sentiment trends in community water fluoridation (CWF) discussions on 'X' from 2014 to 2023 and generated a five-year forecast to anticipate future shifts. METHODS: Sentiment analysis was con... read more 

Apparent Diffusion Coefficient Magnetic Resonance Imaging as a Predictive Biomarker for Hypoxia, Treatment De-escalation, and Recurrence in Human Papillomavirus-Associated Oropharyngeal Cancer.

International journal of radiation oncology, biology, physics
PURPOSE: To evaluate whether quantitative diffusion-weighted magnetic resonance imaging derived apparent diffusion coefficient (ADC) parametric values of nodal disease can identify nodal recurrence (NR) risk and distinguish patients with human papill... read more 

Deep Learning-Based Motion-Compensated Reconstruction for Accelerating 4-Dimensional Magnetic Resonance Fingerprinting.

International journal of radiation oncology, biology, physics
PURPOSE: To develop and validate DeepMocor, a deep learning-based method for motion-compensated 4-dimensional magnetic resonance fingerprinting (4D-MRF) reconstruction to accelerate conventional 4D-MRF reconstruction, enabling more efficient clinical... read more 

Uncovering predictors of bipolar II conversion to bipolar I: A machine learning analysis of national health records in Taiwan.

Journal of affective disorders
BACKGROUND: Bipolar II disorder (BD-II) can progress to bipolar I disorder (BD-I), carrying profound psychosocial consequences. However, limited research has investigated the transition from BD-II to BD-I. Our study uses machine learning to predict t... read more 

Artificial intelligence-driven precision treatment of reproductive medicine-related diseases: the optimal protocol choice for IVF-ET.

Journal of advanced research
INTRODUCTION: Optimal ovarian stimulation (OS) selection is critical for IVF success, but expert-based decisions often lack consistency in outcomes, cost-efficiency, and personalization, highlighting the need for more individualized and data-driven a... read more 

Bulk metagenomics and machine learning unravels nitrogen metabolism patterns in extreme-temperature marine environments.

Bioresource technology
The nitrogen metabolism genes and associated microorganisms in polar oceans and hydrothermal vents remain insufficiently studied. In this study, metagenomic data were analyzed to characterize the geographical and biological features of 16 key nitroge... read more 

IFCNN-based fusion of GAF and MTF encoded near-infrared spectral images for quantitative analysis of microplastics.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Microplastics pollution has become the second-largest global environmental issue. Therefore, accurate and rapid quantification of microplastics is of great significance. This study proposed a novel quantitative approach that integrated near-infrared ... read more 

Comparative evaluation of ChatGPT and Gemini in brain-computer interfaces patient education: A multi-dimensional analysis of reliability, accuracy, comprehensibility, and readability.

International journal of medical informatics
BACKGROUND: Brain-Computer Interfaces (BCI) are a type of life-altering neurotechnology, but their inherent complexity poses significant challenges to patient education. Large Language Models (LLMs), such as ChatGPT and Gemini, offer new possibilitie... read more 

Use of indirect methods and machine learning algorithms for the estimation of reference intervals, taking cortisol measurements as an example.

Clinical chemistry and laboratory medicine
OBJECTIVES: This study aims to determine reliable reference intervals (RIs) for total cortisol (TC) in adults considering the effects of both age and blood collection time, using indirect methods and machine learning approaches. METHODS: Serum TC res... read more