AIMC Topic: Machine Learning

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Innovative Identification of Substance Use Predictors: Machine Learning in a National Sample of Mexican Children.

Prevention science : the official journal of the Society for Prevention Research
Machine learning provides a method of identifying factors that discriminate between substance users and non-users potentially improving our ability to match need with available prevention services within context with limited resources. Our aim was to...

Validation of Deep Convolutional Neural Network-based algorithm for detection of diabetic retinopathy - Artificial intelligence versus clinician for screening.

Indian journal of ophthalmology
PURPOSE: Deep learning is a newer and advanced subfield in artificial intelligence (AI). The aim of our study is to validate a machine-based algorithm developed based on deep convolutional neural networks as a tool for screening to detect referable d...

Artificial Intelligence in Anesthesiology: Current Techniques, Clinical Applications, and Limitations.

Anesthesiology
Artificial intelligence has been advancing in fields including anesthesiology. This scoping review of the intersection of artificial intelligence and anesthesia research identified and summarized six themes of applications of artificial intelligence ...

Ensembled machine learning framework for drug sensitivity prediction.

IET systems biology
Drug sensitivity prediction is one of the critical tasks involved in drug designing and discovery. Recently several online databases and consortiums have contributed to providing open access to pharmacogenomic data. These databases have helped in dev...

Improvement in prediction of antigenic epitopes using stacked generalisation: an ensemble approach.

IET systems biology
The major intent of peptide vaccine designs, immunodiagnosis and antibody productions is to accurately identify linear B-cell epitopes. The determination of epitopes through experimental analysis is highly expensive. Therefore, it is desirable to dev...

Can Machine Learning Improve Screening for Targeted Delinquency Prevention Programs?

Prevention science : the official journal of the Society for Prevention Research
The cost-effectiveness of targeted delinquency prevention programs for children depends on the accuracy of the screening process. Screening accuracy is often poor, resulting in wasted resources and missed opportunities to avert negative outcomes. Thi...