AIMC Topic: Machine Learning

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The Predictive Value of Basic Laparoscopic Evaluations on Complex Cases Using the Society for Improving Medical Procedural Learning Database.

The Journal of surgical research
INTRODUCTION: The transference of technical skills from basic to complex procedures is assumed-but untested-during training and board certification. We examine whether resident performance on frequently performed, basic laparoscopic procedures can pr...

Predicting Weaning Weight of Romanov Lambs From Biometric Measurements Before Weaning Age Using Machine Learning Algorithms.

Veterinary medicine and science
BACKGROUND: Machine learning systems learn from historical data to forecast future outcomes. In the context of livestock farming, machine learning can be utilized to predict variables such as growth rates, milk production and breeding success by anal...

Machine learning in neuroimaging and computational pathophysiology of Parkinson's disease: A comprehensive review and meta-analysis.

Asian journal of psychiatry
In recent years, machine learning and deep learning have shown potential for improving Parkinson's disease (PD) diagnosis, one of the most common neurodegenerative diseases. This comprehensive analysis examines machine learning and deep learning-base...

Brain Fractal Dimension and Machine Learning can predict first-episode psychosis and risk for transition to psychosis.

Computers in biology and medicine
Although there are notable structural abnormalities in the brain associated with psychotic diseases, it is still unclear how these abnormalities relate to clinical presentation. However, the fractal dimension (FD), which offers details on the complex...

Advancing emotion recognition with Virtual Reality: A multimodal approach using physiological signals and machine learning.

Computers in biology and medicine
INTRODUCTION: Emotion recognition systems have traditionally relied on basic visual elicitation. Virtual reality (VR) offers an immersive alternative that better resembles real-world emotional experiences.

Integration of metabolomics and machine learning for precise management and prevention of cardiometabolic risk in Asians.

Clinical nutrition (Edinburgh, Scotland)
Rapid changes in dietary patterns have led to a rise in cardiometabolic diseases (CMDs) worldwide, highlighting the urgent need for effective dietary strategies to address the health issues. Compared to Caucasians, Asians are more susceptible to CMDs...

Machine learning in biofluid mechanics: A review of recent developments.

Computers in biology and medicine
This review paper comprehensively examines recent advancements in machine learning (ML) applications within biofluid mechanics, with a targeted focus on enabling clinically actionable diagnostics and simulations. It demonstrates how ML, and in partic...

A novel Harris Hawks Optimization-based clustering method for elucidating genetic associations in osteoarthritis and Diverse Cancer Types.

Computers in biology and medicine
Considering the high incidence of osteoarthritis (OA), especially of the knee and hip, this study explores the possible genetic associations between OA and cancer types, including cancers of the bladder, kidney, breast, and prostate. The objective of...

Letter to the Editor regarding "Prediction of PFAS bioaccumulation in different plant tissues with machine learning models based on molecular fingerprints" by Song et al. (2024), Sci. Total Environ. 950 175091.

The Science of the total environment
Song et al. (2024), "Prediction of PFAS bioaccumulation in different plant tissues with machine learning models based on molecular fingerprints," employed machine learning methods, such as XGBoost and SHapley Additive exPlanations (SHAP), to predict ...

Current and future directions for the use of handheld fundus cameras in telehealth.

Expert review of medical devices
INTRODUCTION: A shortage of trained retinal specialists has created a growing need for a telehealth retinal screening alternative. Recent developments in handheld fundus cameras, enhanced by artificial intelligence (AI) and machine learning (ML) meth...