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, ...
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...
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...
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...
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...
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...
Advancements in diagnostic technology are required to improve patient outcomes and facilitate early diagnosis, as breast cancer is a substantial global health concern. This research discusses the creation of a unique Deep Learning (DL) Ensemble Deep ...
Preeclampsia (PE) and fetal growth restriction (FGR) complicate 5-10% of pregnancies and are major causes of maternal and fetal morbidity and mortality. Here we demonstrate that measuring circulating cell-free RNAs (cfRNAs) from maternal plasma can a...
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...
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...
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