AIMC Topic: Machine Learning

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Macrolide combination therapy for patients hospitalised with community-acquired pneumonia? An individualised approach supported by machine learning.

The European respiratory journal
BACKGROUND: The role of macrolide/β-lactam combination therapy in community-acquired pneumonia (CAP) of moderate severity is a matter of debate. Macrolides expand the coverage to atypical pathogens and attenuate pulmonary inflammation, but have been ...

From What to How: An Initial Review of Publicly Available AI Ethics Tools, Methods and Research to Translate Principles into Practices.

Science and engineering ethics
The debate about the ethical implications of Artificial Intelligence dates from the 1960s (Samuel in Science, 132(3429):741-742, 1960. https://doi.org/10.1126/science.132.3429.741 ; Wiener in Cybernetics: or control and communication in the animal an...

Artificial intelligence applications for thoracic imaging.

European journal of radiology
Artificial intelligence is a hot topic in medical imaging. The development of deep learning methods and in particular the use of convolutional neural networks (CNNs), have led to substantial performance gain over the classic machine learning techniqu...

Current state of science in machine learning methods for automatic infant pain evaluation using facial expression information: study protocol of a systematic review and meta-analysis.

BMJ open
INTRODUCTION: Infants can experience pain similar to adults, and improperly controlled pain stimuli could have a long-term adverse impact on their cognitive and neurological function development. The biggest challenge of achieving good infant pain co...

Time-resolved evaluation of compound repositioning predictions on a text-mined knowledge network.

BMC bioinformatics
BACKGROUND: Computational compound repositioning has the potential for identifying new uses for existing drugs, and new algorithms and data source aggregation strategies provide ever-improving results via in silico metrics. However, even with these a...

Effective machine-learning assembly for next-generation amplicon sequencing with very low coverage.

BMC bioinformatics
BACKGROUND: In short-read DNA sequencing experiments, the read coverage is a key parameter to successfully assemble the reads and reconstruct the sequence of the input DNA. When coverage is very low, the original sequence reconstruction from the read...

Machine-learning based patient classification using Hepatitis B virus full-length genome quasispecies from Asian and European cohorts.

Scientific reports
Chronic infection with Hepatitis B virus (HBV) is a major risk factor for the development of advanced liver disease including fibrosis, cirrhosis, and hepatocellular carcinoma (HCC). The relative contribution of virological factors to disease progres...

Predicting long-term type 2 diabetes with support vector machine using oral glucose tolerance test.

PloS one
Diabetes is a large healthcare burden worldwide. There is substantial evidence that lifestyle modifications and drug intervention can prevent diabetes, therefore, an early identification of high risk individuals is important to design targeted preven...