AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Translational Research, Biomedical

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sureLDA: A multidisease automated phenotyping method for the electronic health record.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: A major bottleneck hindering utilization of electronic health record data for translational research is the lack of precise phenotype labels. Chart review as well as rule-based and supervised phenotyping approaches require laborious expert...

Applications of machine learning methods in kidney disease: hope or hype?

Current opinion in nephrology and hypertension
PURPOSE OF REVIEW: The universal adoption of electronic health records, improvement in technology, and the availability of continuous monitoring has generated large quantities of healthcare data. Machine learning is increasingly adopted by nephrology...

Artificial Intelligence in Ophthalmology: Evolutions in Asia.

Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)
Artificial intelligence (AI) has been studied in ophthalmology since availability of digital information in ophthalmic care. The significant turning point was availability of commercial digital color fundus photography in the late 1990s, which caused...

An outcome model approach to transporting a randomized controlled trial results to a target population.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Participants enrolled into randomized controlled trials (RCTs) often do not reflect real-world populations. Previous research in how best to transport RCT results to target populations has focused on weighting RCT data to look like the tar...

canSAR: update to the cancer translational research and drug discovery knowledgebase.

Nucleic acids research
canSAR (http://cansar.icr.ac.uk) is a public, freely available, integrative translational research and drug discovery knowlegebase. canSAR informs researchers to help solve key bottlenecks in cancer translation and drug discovery. It integrates genom...

Considerations for automated machine learning in clinical metabolic profiling: Altered homocysteine plasma concentration associated with metformin exposure.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
With the maturation of metabolomics science and proliferation of biobanks, clinical metabolic profiling is an increasingly opportunistic frontier for advancing translational clinical research. Automated Machine Learning (AutoML) approaches provide ex...