AIMC Topic: Machine Learning

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Develop machine learning-based regression predictive models for engineering protein solubility.

Bioinformatics (Oxford, England)
MOTIVATION: Protein activity is a significant characteristic for recombinant proteins which can be used as biocatalysts. High activity of proteins reduces the cost of biocatalysts. A model that can predict protein activity from amino acid sequence is...

Artificial Intelligence and Applications in PM&R.

American journal of physical medicine & rehabilitation
Artificial intelligence methods are being applied broadly in society and increasingly in health care and research. Machine learning, a subset of artificial intelligence, represents the study of algorithms that improve automatically with experience. T...

[A review of machine learning in tumor radiotherapy].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Radiotherapy is one of the main treatments for tumor with increasingly high request for technique precision and the equipment stability. Machine learning may bring radiotherapy simplicity, individualization and precision, and may improve the automati...

Risk stratification of cervical lesions using capture sequencing and machine learning method based on HPV and human integrated genomic profiles.

Carcinogenesis
From initial human papillomavirus (HPV) infection and precursor stages, the development of cervical cancer takes decades. High-sensitivity HPV DNA testing is currently recommended as primary screening method for cervical cancer, whereas better triage...

Simulation-assisted machine learning.

Bioinformatics (Oxford, England)
MOTIVATION: In a predictive modeling setting, if sufficient details of the system behavior are known, one can build and use a simulation for making predictions. When sufficient system details are not known, one typically turns to machine learning, wh...

Classical scoring functions for docking are unable to exploit large volumes of structural and interaction data.

Bioinformatics (Oxford, England)
MOTIVATION: Studies have shown that the accuracy of random forest (RF)-based scoring functions (SFs), such as RF-Score-v3, increases with more training samples, whereas that of classical SFs, such as X-Score, does not. Nevertheless, the impact of the...

[An overview of validation methods based on the medical claims database].

Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi
Medical claims database is an important source of data for studying the characteristics, and burden of diseases, to provide a basis for the development of policy on management. The database is usually used to identify patients through International C...

Computational Neuroethology: A Call to Action.

Neuron
The brain is worthy of study because it is in charge of behavior. A flurry of recent technical advances in measuring and quantifying naturalistic behaviors provide an important opportunity for advancing brain science. However, the problem of understa...

Responsible Use of Machine Learning Classifiers in Clinical Practice.

Journal of law and medicine
Machine learning models are increasingly being used in clinical settings for diagnostic and treatment recommendations, across a variety of diseases and diagnostic methods. To conceptualise how physicians can use them responsibly, and what the standar...