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Galactose-Induced Cataracts in Rats: A Machine Learning Analysis.

International journal of medical sciences
Rat models are widely used to study cataracts due to their cost-effectiveness and prominent physiological and genetic similarities to humans The objective of this study was to identify genes involved in cataractogenesis due to galactose exposure in ...

Unlocking Dreams and Dreamless Sleep: Machine Learning Classification With Optimal EEG Channels.

BioMed research international
Research suggests that dreams play a role in the regulation of emotional processing and memory consolidation; electroencephalography (EEG) is useful for studying them, but manual annotation is time-consuming and prone to bias. This study was aimed at...

Research on the construction of a sustainable scientific research capability evaluation model for university teachers based on the T-S fuzzy neural network.

PloS one
INTRODUCTION: This study aims to enhance educational quality and academic standards by proposing a model based on critical research ability indicators to objectively evaluate the sustainable scientific research capabilities of university teachers.

The cathartic dream: Using a large language model to study a new type of functional dream in healthy and clinical populations.

Journal of sleep research
According to some theories of emotion regulation, dreams could modify negative emotions and ultimately reduce their intensity. We introduce here the idea of cathartic dream, a specific and separate type of emotional dream, which is characterized by a...

Methods for estimating resting energy expenditure in intensive care patients: A comparative study of predictive equations with machine learning and deep learning approaches.

Computer methods and programs in biomedicine
BACKGROUND: Accurate estimation of resting energy expenditure (REE) is critical for guiding nutritional therapy in critically ill patients. While indirect calorimetry (IC) is the gold standard for REE measurement, it is not routinely feasible in clin...

Generating synthetic past and future states of Knee Osteoarthritis radiographs using Cycle-Consistent Generative Adversarial Neural Networks.

Computers in biology and medicine
Knee Osteoarthritis (KOA), a leading cause of disability worldwide, is challenging to detect early due to subtle radiographic indicators. Diverse, extensive datasets are needed but are challenging to compile because of privacy, data collection limita...

An efficient artificial neural network-based optimization techniques for the early prediction of coronary heart disease: comprehensive analysis.

Scientific reports
Coronary heart disease (CHD) is the world's leading cause of death, contributing to a high mortality rate. This emphasizes the requirement for an advanced decision support system in order to evaluate the risk of CHD. This study presents an Artificial...

Human-AI collaboration for ultrasound diagnosis of thyroid nodules: a clinical trial.

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
PURPOSE: This clinical trial examined how the articifial intelligence (AI)-based diagnostics system S-Detect for Thyroid influences the ultrasound diagnostic work-up of thyroid ultrasound (US) performed by different US users in clinical practice and ...

Ultrasonic-Based Radiomics Signature With Machine Learning for Differentiating Prognostic Subsets of Pediatric Peripheral Neuroblastic Tumors: A Retrospective Study.

Ultrasound in medicine & biology
OBJECTIVE: To construct and select a better model based on ultrasonic-based radiomics features and clinical characteristics for prognostic subsets of pediatric neuroblastic tumors.

Towards a latent space cartography of subjective experience in mental health.

Psychiatry and clinical neurosciences
AIMS: The way that individuals subjectively experience the world greatly influences their own mental well-being. However, it remains a considerable challenge to precisely characterize the breadth and depth of such experiences. One persistent problem ...