AIMC Topic: Machine Learning

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Semantic classification of Indonesian consumer health questions.

Journal of biomedical semantics
PURPOSE: Online consumer health forums serve as a way for the public to connect with medical professionals. While these medical forums offer a valuable service, online Question Answering (QA) forums can struggle to deliver timely answers due to the l...

Ecological epidemiology insights into clonorchiosis endemicity in Guangxi, China and Vietnam: a comprehensive machine learning analysis.

International journal of health geographics
BACKGROUND: Clonorchis sinensis, the liver fluke responsible for clonorchiosis, presents a persistent public health burden in Guangxi (Southern China) and Vietnam. Its transmission is influenced by a complex interplay of ecological, climatic, and soc...

Identification of age-specific risk factors for hyperuricemia: a machine learning-driven stratified analysis in health examination cohorts.

BMC medical informatics and decision making
BACKGROUND: Hyperuricemia (HUA) as a global public health challenge, although its overall epidemiological characteristics have been widely reported, its age-specific risk pattern remains controversial. This study aims to reveal the risk factors of HU...

Machine Learning Predicts Drug Release Profiles and Kinetic Parameters Based on Tablets' Formulations.

The AAPS journal
Direct compression (DC) remains a popular manufacturing technology for producing solid dosage forms. However, the formulation optimisation is a laborious process, costly and time-consuming. The aim of this study was to determine whether machine learn...

Data Transformation to Advance AI/ML Research and Implementation in Primary Care.

Annals of family medicine
Artificial intelligence and machine learning (AI/ML) in health care is accelerating at a breathtaking pace. As the largest health care delivery platform, primary care is where the power, opportunity, and future of AI/ML are most likely to be realized...

Predicting Missed Appointments in Primary Care: A Personalized Machine Learning Approach.

Annals of family medicine
PURPOSE: Factors influencing missed appointments are complex and difficult to anticipate and intervene against. To optimize appointment adherence, we aimed to use personalized machine learning and big data analytics to predict the risk of and contrib...

In silico prediction of variant effects: promises and limitations for precision plant breeding.

TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik
Sequence-based AI models show great potential for prediction of variant effects at high resolution, but their practical value in plant breeding remains to be confirmed through rigorous validation studies. Plant breeding has traditionally relied on ph...

Machine learning-based prediction of nitrogen-fixing efficiency in Cowpea rhizobia from the Brazilian semiarid.

World journal of microbiology & biotechnology
This study explores the potential of machine learning to predict nitrogen fixation efficiency in rhizobia strains associated with cowpea (Vigna unguiculata), aiming to optimize bioinoculant selection for sustainable agriculture. Eight native strains ...

Integrated multi-omics analysis and machine learning refine molecular subtypes and prognosis in hepatocellular carcinoma through O-linked glycosylation genes.

Functional & integrative genomics
O-glycosylation significantly influences cellular physiological processes and disease regulation by modulating the structure, function, and stability of proteins. However, there is a notable gap in research focusing on O-glycosylation in relation to ...

EEG-based speech imagery decoding by dynamic hypergraph learning within projected and selected feature subspaces.

Journal of neural engineering
Speech imagery is a nascent paradigm that is receiving widespread attention in current brain-computer interface (BCI) research. By collecting the electroencephalogram (EEG) data generated when imagining the pronunciation of a sentence or word in huma...