AIMC Topic: Machine Learning

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Using Machine Learning to Identify Suicide Risk: A Classification Tree Approach to Prospectively Identify Adolescent Suicide Attempters.

Archives of suicide research : official journal of the International Academy for Suicide Research
This study applies classification tree analysis to prospectively identify suicide attempters among a large adolescent community sample, to demonstrate the strengths and limitations of this approach for risk identification. Data were drawn from the Na...

Sleep stage classification using covariance features of multi-channel physiological signals on Riemannian manifolds.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The recognition of many sleep related pathologies highly relies on an accurate classification of sleep stages. Clinically, sleep stages are usually labelled by sleep experts through visually inspecting the whole-night polyso...

Machine learning modelling for the ultrasonication-mediated disruption of recombinant E. coli for the efficient release of nitrilase.

Ultrasonics
The ultrasonication-mediated cell disruption of recombinant E. coli was modeled using three machine learning techniques namely Multiple linear regression (MLR), Multi-layer perceptron (MLP) and Sequential minimal optimization (SMO). The four attribut...

Design and Implementation of a Machine Learning Based EEG Processor for Accurate Estimation of Depth of Anesthesia.

IEEE transactions on biomedical circuits and systems
Accurate monitoring of the depth of anesthesia (DoA) is essential for intraoperative and postoperative patient's health. Commercially available electroencephalograph (EEG)-based DoA monitors are recommended only for certain anesthetic drugs and speci...

Early Detection of Depression: Social Network Analysis and Random Forest Techniques.

Journal of medical Internet research
BACKGROUND: Major depressive disorder (MDD) or depression is among the most prevalent psychiatric disorders, affecting more than 300 million people globally. Early detection is critical for rapid intervention, which can potentially reduce the escalat...

Identifying genetic determinants of complex phenotypes from whole genome sequence data.

BMC genomics
BACKGROUND: A critical goal in biology is to relate the phenotype to the genotype, that is, to find the genetic determinants of various traits. However, while simple monofactorial determinants are relatively easy to identify, the underpinnings of com...

An advanced approach to identify antimicrobial peptides and their function types for penaeus through machine learning strategies.

BMC bioinformatics
BACKGROUND: Antimicrobial peptides (AMPs) are essential components of the innate immune system and can protect the host from various pathogenic bacteria. The marine environment is known to be one of the richest sources for AMPs. Effective usage of AM...

Development of machine learning algorithms for prediction of prolonged opioid prescription after surgery for lumbar disc herniation.

The spine journal : official journal of the North American Spine Society
BACKGROUND CONTEXT: Spine surgery has been identified as a risk factor for prolonged postoperative opioid use. Preoperative prediction of opioid use could improve risk stratification, shared decision-making, and patient counseling before surgery.

A Review of Machine Learning Techniques for Keratoconus Detection and Refractive Surgery Screening.

Seminars in ophthalmology
Various machine learning techniques have been developed for keratoconus detection and refractive surgery screening. These techniques utilize inputs from a range of corneal imaging devices and are built with automated decision trees, support vector ma...

Cascade interpolation learning with double subspaces and confidence disturbance for imbalanced problems.

Neural networks : the official journal of the International Neural Network Society
In this paper, a new ensemble framework named Cascade Interpolation Learning with Double subspaces and Confidence disturbance (CILDC) is designed for the imbalanced classification problems. Developed from the Cascade Forest of the Deep Forest which i...