AIMC Topic: Humans

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Osteoporotic hip fracture prediction from risk factors available in administrative claims data - A machine learning approach.

PloS one
OBJECTIVE: Hip fractures are among the most frequently occurring fragility fractures in older adults, associated with a loss of quality of life, high mortality, and high use of healthcare resources. The aim was to apply the superlearner method to pre...

In reply to 'clinical biochemistry test eliminator providing cost-effectiveness with five algorithms': the Casablanca strategy.

Acta clinica Belgica
In this journal, Ataman Gönel recently demonstrated that elimination of requested unnecessary tests by means of algorithms in an artificial intelligence program may contribute to the cost-effectiveness of medicine. However, test ordering is an essent...

Predictive regression modeling with MEG/EEG: from source power to signals and cognitive states.

NeuroImage
Predicting biomedical outcomes from Magnetoencephalography and Electroencephalography (M/EEG) is central to applications like decoding, brain-computer-interfaces (BCI) or biomarker development and is facilitated by supervised machine learning. Yet, m...

Using machine learning to improve our understanding of injury risk and prediction in elite male youth football players.

Journal of science and medicine in sport
OBJECTIVES: The purpose of this study was to examine whether the use of machine learning improved the ability of a neuromuscular screen to identify injury risk factors in elite male youth football players.

Ultrasound Deep Learning for Wall Segmentation and Near-Wall Blood Flow Measurement.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Studies of medical flow imaging have technical limitations for accurate analysis of blood flow dynamics and vessel wall interaction at arteries. We propose a new deep learning-based boundary detection and compensation (DL-BDC) technique in ultrasound...

Machine learning to quantify habitual physical activity in children with cerebral palsy.

Developmental medicine and child neurology
AIM: To investigate whether activity-monitors and machine learning models could provide accurate information about physical activity performed by children and adolescents with cerebral palsy (CP) who use mobility aids for ambulation.

The Future is Knocking: How Artificial Intelligence Will Fundamentally Change Psychiatry.

Academic psychiatry : the journal of the American Association of Directors of Psychiatric Residency Training and the Association for Academic Psychiatry

A web-based automated machine learning platform to analyze liquid biopsy data.

Lab on a chip
Liquid biopsy (LB) technologies continue to improve in sensitivity, specificity, and multiplexing and can measure an ever growing library of disease biomarkers. However, clinical interpretation of the increasingly large sets of data these technologie...