AIMC Topic: Machine Learning

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Current uses, emerging applications, and clinical integration of artificial intelligence in neuroradiology.

Reviews in the neurosciences
Artificial intelligence (AI) is a branch of computer science with a variety of subfields and techniques, exploited to serve as a deductive tool that performs tasks originally requiring human cognition. AI tools and its subdomains are being incorporat...

Predicting carcass cut yields in cattle from digital images using artificial intelligence.

Meat science
Deep Learning (DL) has proven to be a successful tool for many image classification problems but has yet to be applied to carcass images. The aim of this study was to train DL models to predict carcass cut yields and compare predictions to more stand...

Preoperative prediction of postoperative urinary retention in lumbar surgery: a comparison of regression to multilayer neural network.

Journal of neurosurgery. Spine
OBJECTIVE: Postoperative urinary retention (POUR) is a common complication after spine surgery and is associated with prolongation of hospital stay, increased hospital cost, increased rate of urinary tract infection, bladder overdistention, and auton...

Reducing variability of breast cancer subtype predictors by grounding deep learning models in prior knowledge.

Computers in biology and medicine
Deep learning neural networks have improved performance in many cancer informatics problems, including breast cancer subtype classification. However, many networks experience underspecificationwheremultiplecombinationsofparametersachievesimilarperfor...

Substituting clinical features using synthetic medical phrases: Medical text data augmentation techniques.

Artificial intelligence in medicine
Biomedical natural language processing (NLP) has an important role in extracting consequential information in medical discharge notes. Detecting meaningful features from unstructured notes is a challenging task in medical document classification. The...

Geometric and biomechanical modeling aided by machine learning improves the prediction of growth and rupture of small abdominal aortic aneurysms.

Scientific reports
It remains difficult to predict when which patients with abdominal aortic aneurysm (AAA) will require surgery. The aim was to study the accuracy of geometric and biomechanical analysis of small AAAs to predict reaching the threshold for surgery, diam...

Predicting drug sensitivity of cancer cells based on DNA methylation levels.

PloS one
Cancer cell lines, which are cell cultures derived from tumor samples, represent one of the least expensive and most studied preclinical models for drug development. Accurately predicting drug responses for a given cell line based on molecular featur...

Deep Tobit networks: A novel machine learning approach to microeconometrics.

Neural networks : the official journal of the International Neural Network Society
Tobit models (also called as "censored regression models" or classified as "sample selection models" in microeconometrics) have been widely applied to microeconometric problems with censored outcomes. However, due to their linear parametric settings ...

Exploring the Predictability of Temperatures in a Scaled Model of a Smarthome.

Sensors (Basel, Switzerland)
In modern smarthomes, temperature regulation is achieved through a mix of traditional and emergent technologies including air conditioning, heating, intelligent utilization of the effects of sun, wind, and shade as well as using stored heat and cold....