AIMC Topic: Machine Learning

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Performance comparison of machine learning models used for predicting subclinical mastitis in dairy cows: Bagging, boosting, stacking, and super-learner ensembles versus single machine learning models.

Journal of dairy science
Mastitis has a substantial impact on the dairy industry across the world, causing dairy producers to suffer losses due to the reduced quality and quantity of produced milk. A further problem, related to this issue, is the excessive use of antibiotics...

Enhancing and improving the performance of imbalanced class data using novel GBO and SSG: A comparative analysis.

Neural networks : the official journal of the International Neural Network Society
Class imbalance problem (CIP) in a dataset is a major challenge that significantly affects the performance of Machine Learning (ML) models resulting in biased predictions. Numerous techniques have been proposed to address CIP, including, but not limi...

Protocol to train a support vector machine for the automatic curation of bacterial cell detections in microscopy images.

STAR protocols
Manual curation of bacterial cell detections in microscopy images remains a time-consuming and laborious task. This work offers a comprehensive, step-by-step tutorial on training a support vector machine to autonomously distinguish between good and b...

A review of traditional Chinese medicine diagnosis using machine learning: Inspection, auscultation-olfaction, inquiry, and palpation.

Computers in biology and medicine
Traditional Chinese medicine (TCM) is an essential part of the Chinese medical system and is recognized by the World Health Organization as an important alternative medicine. As an important part of TCM, TCM diagnosis is a method to understand a pati...

Optimised stacked machine learning algorithms for genomics and genetics disorder detection in the healthcare industry.

Functional & integrative genomics
With recent advances in precision medicine and healthcare computing, there is an enormous demand for developing machine learning algorithms in genomics to enhance the rapid analysis of disease disorders. Technological advancement in genomics and imag...

A Laplacian Pyramid Based Generative H&E Stain Augmentation Network.

IEEE transactions on medical imaging
Hematoxylin and Eosin (H&E) staining is a widely used sample preparation procedure for enhancing the saturation of tissue sections and the contrast between nuclei and cytoplasm in histology images for medical diagnostics. However, various factors, su...

Automating the assessment of multicultural orientation through machine learning and natural language processing.

Psychotherapy (Chicago, Ill.)
Recent scholarship has highlighted the value of therapists adopting a multicultural orientation (MCO) within psychotherapy. A newly developed performance-based measure of MCO capacities exists (MCO-performance task [MCO-PT]) in which therapists respo...