The algorithms then learn from the data and churn out either a probability or a classification. Although ai possesses the capability to revolutionize several fields of medicine it still has limitations and cannot replace a bedside physician.
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Artificial intelligence algorithms offer the possibility of identifying genetic weaknesses in drug resistant strains of bacteria.
Medical field artificial intelligence in medicine. Ai has already been used successfully in all of the 4 main stages in drug development. This has the potential to shave off years of work and hundreds of millions in investments. Artificial intelligence has led to significant improvements in areas of healthcare such as medical imaging automated clinical decision making diagnosis prognosis and more.
Most applications of ai in medicine read in some type of data either numerical such as heart rate or blood pressure or image based such as mri scans or images of biopsy tissue samples as an input. Speeding up clinical trials. Identifying targets for intervention.
Research out of the argonne national laboratory uses an ai technique called extreme gradient boosting xgboost to explore the possibility of performing targeted treatments against these superbugs.
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