AIMC Topic: Machine Learning

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Comparing stress prediction models using smartwatch physiological signals and participant self-reports.

Computer methods and programs in biomedicine May 30, 2021
Recent advances in wearable technology have facilitated the non-obtrusive monitoring of physiological signals, creating opportunities to monitor and predict stress. Researchers have utilized machine learning methods using these physiological signals ...
Humans Machine Learning Wearable Electronic Devices Logistic Models Support Vector Machine Self Report
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Biased accuracy in multisite machine-learning studies due to incomplete removal of the effects of the site.

Psychiatry research. Neuroimaging May 29, 2021
Brain MRI researchers conducting multisite studies, such as within the ENIGMA Consortium, are very aware of the importance of controlling the effects of the site (EoS) in the statistical analysis. Conversely, authors of the novel machine-learning MRI...
Neuroimaging Humans Machine Learning Sensitivity and Specificity Magnetic Resonance Imaging
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A digital highway for data fluidity and data equity in precision medicine.

Biochimica et biophysica acta. Reviews on cancer May 29, 2021
Recent technological advances continue to expand the universe of big data in biomedicine along the four axes of variety, veracity, volume, and velocity, fueling innovations in research and discovery while transforming care delivery. These advances al...
Humans Artificial Intelligence Machine Learning Precision Medicine Big Data Data Mining Diffusion of Innovation
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i4mC-EL: Identifying DNA N4-Methylcytosine Sites in the Mouse Genome Using Ensemble Learning.

BioMed research international May 29, 2021
As one of important epigenetic modifications, DNA N4-methylcytosine (4mC) plays a crucial role in controlling gene replication, expression, cell cycle, DNA replication, and differentiation. The accurate identification of 4mC sites is necessary to und...
Epigenesis, Genetic Cytosine Base Sequence Machine Learning DNA Animals Genome Algorithms DNA Methylation Genetic Techniques ROC Curve Reproducibility of Results Area Under Curve Bayes Theorem Mice Internet Computational Biology Data Mining
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Improving Stroke Risk Prediction in the General Population: A Comparative Assessment of Common Clinical Rules, a New Multimorbid Index, and Machine-Learning-Based Algorithms.

Thrombosis and haemostasis May 28, 2021
BACKGROUND: There are few large studies examining and predicting the diversified cardiovascular/noncardiovascular comorbidity relationships with stroke. We investigated stroke risks in a very large prospective cohort of patients with multimorbidity, ...
Adult Male Middle Aged Risk Assessment Risk Factors Aged Aged, 80 and over Stroke Medicare Multimorbidity Insurance Claim Review Adolescent Cohort Studies Logistic Models United States Machine Learning Algorithms Humans Prospective Studies Female
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Multiple machine learning models combined with virtual screening and molecular docking to identify selective human ALDH1A1 inhibitors.

Journal of molecular graphics & modelling May 28, 2021
Aldehyde dehydrogenases (ALDHs) are the enzymes of oxidoreductase family that are responsible for the aldehyde metabolism. The unbalanced expression of these enzymes may be associated with a variety of disease conditions including cancers. ALDH1A1 is...
Molecular Docking Simulation Aldehyde Dehydrogenase Aldehyde Dehydrogenase 1 Family Retinal Dehydrogenase Humans Machine Learning
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Prediction of Major Complications and Readmission After Lumbar Spinal Fusion: A Machine Learning-Driven Approach.

World neurosurgery May 28, 2021
BACKGROUND: Given the significant cost and morbidity of patients undergoing lumbar fusion, accurate preoperative risk-stratification would be of great utility. We aim to develop a machine learning model for prediction of major complications and readm...
Lumbar Vertebrae Patient Readmission Predictive Value of Tests Area Under Curve Spinal Fusion Male Middle Aged Risk Assessment Postoperative Complications Retrospective Studies Female Risk Factors Aged Humans ROC Curve Machine Learning Logistic Models Algorithms Treatment Outcome Models, Statistical
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The potential of AI in cancer care and research.

Biochimica et biophysica acta. Reviews on cancer May 28, 2021
Current applications of artificial intelligence (AI), machine learning, and deep learning in cancer research and clinical care are highly diverse-from aiding radiologists in reading medical images to predicting oncoprotein folding and dynamics. The l...
National Cancer Institute (U.S.) Machine Learning Biomedical Research Animals Neoplasms United States Diffusion of Innovation Medical Oncology Humans Artificial Intelligence
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Spine dynamics in the brain, mental disorders and artificial neural networks.

Nature reviews. Neuroscience May 28, 2021
In the brain, most synapses are formed on minute protrusions known as dendritic spines. Unlike their artificial intelligence counterparts, spines are not merely tuneable memory elements: they also embody algorithms that implement the brain's ability ...
Artificial Intelligence Machine Learning Algorithms Mental Disorders Humans Neural Networks, Computer Memory, Short-Term Reward Synapses Species Specificity Brain Animals Neuronal Plasticity Models, Neurological Mental Processes Neurotransmitter Agents Receptors, Dopamine Dopamine Dendritic Spines Optogenetics
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Predicting Infrared Spectra with Message Passing Neural Networks.

Journal of chemical information and modeling May 28, 2021
Infrared (IR) spectroscopy remains an important tool for chemical characterization and identification. Chemprop-IR has been developed as a software package for the prediction of IR spectra through the use of machine learning. This work serves the dua...
Machine Learning Neural Networks, Computer Software
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