AIMC Topic: Machine Learning

Clear Filters Showing 8561 to 8570 of 34417 articles

A Machine Learning Method for RNA-Small Molecule Binding Preference Prediction.

Journal of chemical information and modeling
The interaction between RNA and small molecules is crucial in various biological functions. Identifying molecules targeting RNA is essential for the inhibitor design and RNA-related studies. However, traditional methods focus on learning RNA sequence...

Predicting multiple sclerosis disease progression and outcomes with machine learning and MRI-based biomarkers: a review.

Journal of neurology
Multiple sclerosis (MS) is a demyelinating neurological disorder with a highly heterogeneous clinical presentation and course of progression. Disease-modifying therapies are the only available treatment, as there is no known cure for the disease. Car...

Mapping Biomaterial Complexity by Machine Learning.

Tissue engineering. Part A
Biomaterials often have subtle properties that ultimately drive their bespoke performance. Given this nuanced structure-function behavior, the standard scientific approach of one experiment at a time or design of experiment methods is largely ineffic...

Developing a Machine Learning 'Smart' Polymerase Chain Reaction Thermocycler Part 2: Putting the Theoretical Framework into Practice.

Genes
The introduction of PCR into forensic science and the rapid increases in the sensitivity, specificity and discrimination power of DNA profiling that followed have been fundamental in shaping the field of forensic biology. Despite these developments, ...

The value of CCTA combined with machine learning for predicting angina pectoris in the anomalous origin of the right coronary artery.

Biomedical engineering online
BACKGROUND: Anomalous origin of coronary artery is a common coronary artery anatomy anomaly. The anomalous origin of the coronary artery may lead to problems such as narrowing of the coronary arteries at the beginning of the coronary arteries and abn...

Harnessing computational tools of the digital era for enhanced infection control.

BMC medical informatics and decision making
This paper explores the potential of artificial intelligence, machine learning, and big data analytics in revolutionizing infection control. It addresses the challenges and innovative approaches in combating infectious diseases and antimicrobial resi...

Mild cognitive impairment prediction based on multi-stream convolutional neural networks.

BMC bioinformatics
BACKGROUND: Mild cognitive impairment (MCI) is the transition stage between the cognitive decline expected in normal aging and more severe cognitive decline such as dementia. The early diagnosis of MCI plays an important role in human healthcare. Cur...

Integrating respiratory microbiome and host immune response through machine learning for respiratory tract infection diagnosis.

NPJ biofilms and microbiomes
At present, the diagnosis of lower respiratory tract infections (LRTIs) is difficult, and there is an urgent need for better diagnostic methods. This study enrolled 136 patients from 2020 to 2021 and collected bronchoalveolar lavage fluid (BALF) spec...

Identifying Psychosocial and Ecological Determinants of Enthusiasm In Youth: Integrative Cross-Sectional Analysis Using Machine Learning.

JMIR public health and surveillance
BACKGROUND: Understanding the factors contributing to mental well-being in youth is a public health priority. Self-reported enthusiasm for the future may be a useful indicator of well-being and has been shown to forecast social and educational succes...

Performance analysis of machine learning models for AQI prediction in Gorakhpur City: a critical study.

Environmental monitoring and assessment
Air pollution and climate change are two complementary forces that directly or indirectly affect the environment's physical, chemical, and biological processes. The air quality index is a parameter defined to cope with this effect of air pollution. T...