AIMC Topic: Machine Learning

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A Survey on Machine Learning Algorithms for the Diagnosis of Breast Masses with Mammograms.

Current medical imaging
Breast cancer is leading cancer among women for the past 60 years. There are no effective mechanisms for completely preventing breast cancer. Rather it can be detected at its earlier stages so that unnecessary biopsy can be reduced. Although there ar...

Predictors of Dementia in the Oldest Old: A Novel Machine Learning Approach.

Alzheimer disease and associated disorders
BACKGROUND: Incidence of dementia increases exponentially with age; little is known about its risk factors in the ninth and 10th decades of life. We identified predictors of dementia with onset after age 85 years in a longitudinal population-based co...

Recent Advances on Antioxidant Identification Based on Machine Learning Methods.

Current drug metabolism
Antioxidants are molecules that can prevent damages to cells caused by free radicals. Recent studies also demonstrated that antioxidants play roles in preventing diseases. However, the number of known molecules with antioxidant activity is very small...

Artificial Intelligence in Cardiovascular Imaging.

Methodist DeBakey cardiovascular journal
The number of cardiovascular imaging studies is growing exponentially, and so is the need to improve clinical workflow efficiency and avoid missed diagnoses. With the availability and use of large datasets, artificial intelligence (AI) has the potent...

EHAI: Enhanced Human Microbe-Disease Association Identification.

Current protein & peptide science
Recently, an increasing number of biological and clinical reports have demonstrated that imbalance of microbial community has the ability to play important roles among several complex diseases concerning human health. Having a good knowledge of disco...

[Information Mathematics for Machine Learning].

Igaku butsuri : Nihon Igaku Butsuri Gakkai kikanshi = Japanese journal of medical physics : an official journal of Japan Society of Medical Physics
This manuscript is a supplement to the machine learning course at JSMP Medical Physics Summer School held in 2019. The idea of Kulbuck-Leibler divergence, a key concept in machine learning, is introduced with mutual information.

Machine-Learning Algorithms Based on Screening Tests for Mild Cognitive Impairment.

American journal of Alzheimer's disease and other dementias
BACKGROUND: The mobile screening test system for mild cognitive impairment (mSTS-MCI) was developed and validated to address the low sensitivity and specificity of the Montreal Cognitive Assessment (MoCA) widely used clinically.

mAML: an automated machine learning pipeline with a microbiome repository for human disease classification.

Database : the journal of biological databases and curation
Due to the concerted efforts to utilize the microbial features to improve disease prediction capabilities, automated machine learning (AutoML) systems aiming to get rid of the tediousness in manually performing ML tasks are in great demand. Here we d...

Evaluation and Prediction of Early Alzheimer's Disease Using a Machine Learning-based Optimized Combination-Feature Set on Gray Matter Volume and Quantitative Susceptibility Mapping.

Current Alzheimer research
BACKGROUND: Because Alzheimer's Disease (AD) has very complicated pattern changes, it is difficult to evaluate it with a specific factor. Recently, novel machine learning methods have been applied to solve limitations.