AI Medical Compendium

[Regression analysis to calculate the time point of ROSC-A feasibility study].

Die Anaesthesiologie Jan 30, 2026

BACKGROUND: A regression model to estimate the duration from the onset of resuscitation efforts to the return of spontaneous circulation (ROSC) could help improving both resuscitation care and the quality control of registries. This study aims to eva... read more

[Artificial intelligence in surgical disciplines: Clinical application, advantages, and potential-a Delphi expert consensus].

Urologie (Heidelberg, Germany) Jan 30, 2026

BACKGROUND: Artificial intelligence (AI) in surgical disciplines has the potential to support all areas of patient care, with the goal of improving treatment quality and patient safety. A group of multidisciplinary experts discussed the current situa... read more

Osteoporosis prediction using lumbar CT Hounsfield units: comparative performance and clinical implications of seven machine learning models.

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society Jan 30, 2026

PURPOSE: This study aimed to evaluate the utility of L1-L4 average Hounsfield Unit (HU) values from lumbar spine computed tomography (CT) in predicting osteoporosis using multiple machine learning (ML) models. METHODS: We retrospectively analyzed 172... read more

ChatGPT performance in orthodontics : Assessment of accuracy and repeatability in patient instruction and management using Global Quality Score.

Journal of orofacial orthopedics = Fortschritte der Kieferorthopadie : Organ/official journal Deutsche Gesellschaft fur Kieferorthopadie Jan 30, 2026

PURPOSE: This study assessed the accuracy and repeatability of the orthodontics-related information generated by Chat Generative Pre-trained Transformer (ChatGPT, model GPT-4o, 18 July 2024, OpenAI, San Francisco, CA, USA) and evaluated its usefulnes... read more

An interpretable machine learning model for predicting survival in pancreatic cancer via SHAP: a multicenter study.

Journal of gastroenterology Jan 30, 2026

BACKGROUND: Existing pancreatic cancer prediction models still have significant limitations until now. This multicenter retrospective study aimed to identify clinical features and develop machine learning models for predicting overall survival (OS) i... read more

Artificial intelligence versus classical scoring systems: a comparative analysis of stone-free prediction after percutaneous nephrolithotomy.

Urolithiasis Jan 30, 2026

This study aimed to compare the predictive performance of traditional stone scoring systems with a large language model based on ChatGPT in estimating stone-free rates following percutaneous nephrolithotomy. A total of 340 patients who underwent the ... read more

Lipid monitoring using non-invasive measurement technologies and machine learning: a systematic review.

Archives of gynecology and obstetrics Jan 30, 2026

BACKGROUND: Cardiovascular diseases (CVD) are the leading cause of death among women, with risk increasing after menopause. Lipid levels are key biomarkers, yet conventional blood tests remain invasive and underutilized. Non-invasive technologies and... read more

Real-world evaluation of an automated EEG spike detection software in a tertiary centre compared to a clinical reference standard.

Journal of neurology Jan 30, 2026

BACKGROUND: Interictal epileptiform discharges (IEDs) are transient spikes or waves that occur in electroencephalography (EEG) records and can help support the diagnosis and classification of epilepsy. High-throughput machine learning models aim to a... read more

Deep Learning and Noninvasive Sensors for Detecting Physiological Dysregulation: A Scoping Review.

Journal of medical systems Jan 30, 2026

Early detection of pain, stress, or hemodynamic instability is key to preventing serious clinical events. In recent years, non-invasive sensors and deep learning algorithms have gained relevance as tools for accurate and continuous monitoring. To map... read more

Local-Hybrid Functional With a Composite Local Mixing Function Built From a Neural Network and a Strong-Correlation Model.

Journal of computational chemistry Jan 30, 2026

Due to their position-dependent admixture of the exact-exchange (EXX) energy density, local hybrid functionals (LHs) enable a flexible balance between reduced self-interaction errors and smaller static-correlation errors, allowing an escape from the ... read more

Artificial Intelligence Medical Compendium