AIMC Topic: Machine Learning

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Advances in AI and machine learning for predictive medicine.

Journal of human genetics
The field of omics, driven by advances in high-throughput sequencing, faces a data explosion. This abundance of data offers unprecedented opportunities for predictive modeling in precision medicine, but also presents formidable challenges in data ana...

Development, validation, and transportability of several machine-learned, non-exercise-based VO prediction models for older adults.

Journal of sport and health science
BACKGROUND: There exist few maximal oxygen uptake (VO) non-exercise-based prediction equations, fewer using machine learning (ML), and none specifically for older adults. Since direct measurement of VO is infeasible in large epidemiologic cohort stud...

A comprehensive review on heart disease prognostication using different artificial intelligence algorithms.

Computer methods in biomechanics and biomedical engineering
Prediction of heart diseases on time is significant in order to preserve life. Many conventional methods have taken efforts on earlier prediction but faced with challenges of higher prediction cost, extended time for computation and complexities with...

Interpretable and Intuitive Machine Learning Approaches for Predicting Disability Progression in Relapsing-Remitting Multiple Sclerosis Based on Clinical and Gray Matter Atrophy Indicators.

Academic radiology
RATIONALE AND OBJECTIVES: To investigate whether clinical and gray matter (GM) atrophy indicators can predict disability in relapsing-remitting multiple sclerosis (RRMS) and to enhance the interpretability and intuitiveness of a predictive machine le...

Synthesis of gadolinium-enhanced glioma images on multisequence magnetic resonance images using contrastive learning.

Medical physics
BACKGROUND: Gadolinium-based contrast agents are commonly used in brain magnetic resonance imaging (MRI), however, they cannot be used by patients with allergic reactions or poor renal function. For long-term follow-up patients, gadolinium deposition...

Segmentation, feature extraction and classification of leukocytes leveraging neural networks, a comparative study.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
The gold standard of leukocyte differentiation is a manual examination of blood smears, which is not only time and labor intensive but also susceptible to human error. As to automatic classification, there is still no comparative study of cell segmen...

Miffi: Improving the accuracy of CNN-based cryo-EM micrograph filtering with fine-tuning and Fourier space information.

Journal of structural biology
Efficient and high-accuracy filtering of cryo-electron microscopy (cryo-EM) micrographs is an emerging challenge with the growing speed of data collection and sizes of datasets. Convolutional neural networks (CNNs) are machine learning models that ha...

GANSamples-ac4C: Enhancing ac4C site prediction via generative adversarial networks and transfer learning.

Analytical biochemistry
RNA modification, N4-acetylcytidine (ac4C), is enzymatically catalyzed by N-acetyltransferase 10 (NAT10) and plays an essential role across tRNA, rRNA, and mRNA. It influences various cellular functions, including mRNA stability and rRNA biosynthesis...

Antibiotic combinations prediction based on machine learning to multicentre clinical data and drug interaction correlation.

International journal of antimicrobial agents
BACKGROUND: With increasing antibiotic resistance and regulation, the issue of antibiotic combination has been emphasised. However, antibiotic combination prescribing lacks a rapid identification of feasibility, while its risk of drug interactions is...

Automatic Prediction of Peak Optical Absorption Wavelengths in Molecules Using Convolutional Neural Networks.

Journal of chemical information and modeling
Molecular design depends heavily on optical properties for applications such as solar cells and polymer-based batteries. Accurate prediction of these properties is essential, and multiple predictive methods exist, from to data-driven techniques. Alt...