AIMC Topic: Machine Learning

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Principal Component Analysis based on Nuclear norm Minimization.

Neural networks : the official journal of the International Neural Network Society
Principal component analysis (PCA) is a widely used tool for dimensionality reduction and feature extraction in the field of computer vision. Traditional PCA is sensitive to outliers which are common in empirical applications. Therefore, in recent ye...

Automatic annotation of surgical activities using virtual reality environments.

International journal of computer assisted radiology and surgery
PURPOSE: Annotation of surgical activities becomes increasingly important for many recent applications such as surgical workflow analysis, surgical situation awareness, and the design of the operating room of the future, especially to train machine l...

Mining patient-specific and contextual data with machine learning technologies to predict cancellation of children's surgery.

International journal of medical informatics
BACKGROUND: Last-minute surgery cancellation represents a major wastage of resources and can cause significant inconvenience to patients. Our objectives in this study were: 1) To develop predictive models of last-minute surgery cancellation, utilizin...

On-Site Computed Tomography-Derived Fractional Flow Reserve Using a Machine-Learning Algorithm - Clinical Effectiveness in a Retrospective Multicenter Cohort.

Circulation journal : official journal of the Japanese Circulation Society
BACKGROUND: This study evaluated the diagnostic capability of on-site coronary computed tomography-derived computational fractional flow reserve (CT-FFR) determinations for detecting coronary artery disease (CAD), as assessed by invasive fractional f...

Quantitative Structure-Activity Relationships for Structurally Diverse Chemotypes Having Anti- Activity.

International journal of molecular sciences
Small-molecule compounds that have promising activity against macromolecular targets from occasionally fail when tested in whole-cell phenotypic assays. This outcome can be attributed to many factors, including inadequate physicochemical and pharmac...

Machine learning approaches for risk assessment of peripherally inserted Central catheter-related vein thrombosis in hospitalized patients with cancer.

International journal of medical informatics
OBJECTIVE: The aim of this study was to conduct an effective assessment of peripherally inserted central venous catheter (PICC)-related thrombosis based on machine learning (ML) techniques considering genotype.

Kinetics of -induced gene silencing can be predicted from combinations of epigenetic and genomic features.

Genome research
To initiate X-Chromosome inactivation (XCI), the long noncoding RNA mediates chromosome-wide gene silencing of one X Chromosome in female mammals to equalize gene dosage between the sexes. The efficiency of gene silencing is highly variable across g...

Machine learning approach for distinguishing malignant and benign lung nodules utilizing standardized perinodular parenchymal features from CT.

Medical physics
PURPOSE: Computed tomography (CT) is an effective method for detecting and characterizing lung nodules in vivo. With the growing use of chest CT, the detection frequency of lung nodules is increasing. Noninvasive methods to distinguish malignant from...

Machine Learning Applied to Predicting Microorganism Growth Temperatures and Enzyme Catalytic Optima.

ACS synthetic biology
Enzymes that catalyze chemical reactions at high temperatures are used for industrial biocatalysis, applications in molecular biology, and as highly evolvable starting points for protein engineering. The optimal growth temperature (OGT) of organisms ...