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Simulation-based training in minimally invasive surgical therapies (MIST): current evidence and future directions for artificial intelligence integration-a systematic review by EAU endourology.

World journal of urology
INTRODUCTION: Benign prostatic hyperplasia (BPH) affects a growing proportion of the aging male population. Minimally invasive surgical therapies (MISTs) such as Rezum and UroLift offer effective alternatives to traditional approaches like transureth...

Using machine learning to discover DNA metabolism biomarkers that direct prostate cancer treatment.

Scientific reports
DNA metabolism genes play pivotal roles in the regulation of cellular processes that contribute to cancer progression, immune modulation, and therapeutic response in prostate cancer (PC). Understanding the mechanisms by which these genes influence th...

EEG microstate analysis in children with prolonged disorders of consciousness.

Scientific reports
Prolonged disorders of consciousness (pDoC) in children lack objective and effective diagnostic methods to assess consciousness states, hindering targeted treatment selection and delaying recovery. It remains unclear whether EEG microstate analysis, ...

How challenge stressors affect deviant innovation behavior among Chinese frontline textile workers in the age of artificial intelligence.

Scientific reports
Previous research has examined the impact of internal organizational stress on employee innovation behavior, but recent research has not thoroughly examined whether artificial intelligence can aid frontline workers in innovating beyond their workflow...

Determination of lung cancer exhaled breath biomarkers using machine learning-a new analysis framework.

Scientific reports
Exhaled breath samples of lung cancer patients (LC), tuberculosis (TB) patients and asymptomatic controls (C) were analyzed using gas chromatography-mass spectrometry (GC-MS). Ten volatile organic compounds (VOCs) were identified as possible biomarke...

Machine learning for the prediction of augmented renal clearance (ARC) in patients with sepsis in critical care units.

Scientific reports
This study aims to establish and validate prediction models based on novel machine learning (ML) algorithms for augmented renal clearance (ARC) in critically ill patients with sepsis. Patients with sepsis were extracted from the Medical Information M...

Video-based pupillometry using Fourier Mellin image correlation.

Scientific reports
We introduce a novel method for evaluating the pupil light reflex (PLR) response using digital video recordings. Expensive, specialized devices are replacing traditional penlight tests in emergency and neurotrauma departments, but they are not widely...

Machine learning technology in the classification of glaucoma severity using fundus photographs.

Scientific reports
This study evaluates the performance of a machine learning model in classifying glaucoma severity using color fundus photographs. Glaucoma severity grading was based on the Hodapp-Parrish-Anderson (HPA) criteria incorporating the mean deviation value...

Comprehensive interaction modeling with machine learning improves prediction of disease risk in the UK Biobank.

Nature communications
Understanding how risk factors interact to jointly influence disease risk can provide insights into disease development and improve risk prediction. Here we introduce survivalFM, a machine learning extension to the widely used Cox proportional hazard...

Future Me, a Prospection-Based Chatbot to Promote Mental Well-Being in Youth: Two Exploratory User Experience Studies.

JMIR formative research
BACKGROUND: Digital interventions have been proposed as a solution to meet the growing demand for mental health support. Large language models (LLMs) have emerged as a promising technology for creating more personalized and adaptive mental health cha...