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Cortical surface registration using unsupervised learning.

NeuroImage
Non-rigid cortical registration is an important and challenging task due to the geometric complexity of the human cortex and the high degree of inter-subject variability. A conventional solution is to use a spherical representation of surface propert...

A machine learning approach for mortality prediction only using non-invasive parameters.

Medical & biological engineering & computing
At present, the traditional scoring methods generally utilize laboratory measurements to predict mortality. It results in difficulties of early mortality prediction in the rural areas lack of professional laboratorians and medical laboratory equipmen...

A deep learning method for real-time intraoperative US image segmentation in prostate brachytherapy.

International journal of computer assisted radiology and surgery
PURPOSE: This paper addresses the detection of the clinical target volume (CTV) in transrectal ultrasound (TRUS) image-guided intraoperative for permanent prostate brachytherapy. Developing a robust and automatic method to detect the CTV on intraoper...

Machine-learning approach to predict on-road driving ability in healthy older people.

Psychiatry and clinical neurosciences
AIM: In Japan, fatal traffic accidents due to older drivers are on the rise. Considering that approximately half the older drivers who have caused fatal accidents are cognitively normal healthy people, it has been required to detect older drivers who...

Reproductive outcomes predicted by phase imaging with computational specificity of spermatozoon ultrastructure.

Proceedings of the National Academy of Sciences of the United States of America
The ability to evaluate sperm at the microscopic level, at high-throughput, would be useful for assisted reproductive technologies (ARTs), as it can allow specific selection of sperm cells for in vitro fertilization (IVF). The tradeoff between intrin...

Early detection of type 2 diabetes mellitus using machine learning-based prediction models.

Scientific reports
Most screening tests for T2DM in use today were developed using multivariate regression methods that are often further simplified to allow transformation into a scoring formula. The increasing volume of electronically collected data opened the opport...

Improved myocardial perfusion PET imaging using artificial neural networks.

Physics in medicine and biology
Myocardial perfusion (MP) PET imaging plays a key role in risk assessment and stratification of patients with coronary artery disease. In this work, we proposed a patch-based artificial neural network (ANN) fusion approach that integrates information...

Challenges of machine learning model validation using correlated behaviour data: Evaluation of cross-validation strategies and accuracy measures.

PloS one
Automated monitoring of the movements and behaviour of animals is a valuable research tool. Recently, machine learning tools were applied to many species to classify units of behaviour. For the monitoring of wild species, collecting enough data for t...

Predictors of emergency department opioid administration and prescribing: A machine learning approach.

The American journal of emergency medicine
INTRODUCTION: The opioid epidemic has altered normative clinical perceptions on addressing both acute and chronic pain, particularly within the Emergency Department (ED) setting, where providers are now confronted with balancing pain management and p...