AI able to predict chemotherapy dosages developed

Finding the right chemotherapy dosage is a grueling process of trial and error, leading Stanford University Hospital researchers to train AI to identify correct dosage before treatment begins


A group of researchers from Stanford University Hospital have successfully used AI technology to accurately adjust chemotherapy dosages by identifying those who required a lower dose even before treatment had begun, according to a study published in Nature Scientific Reports.

Finding the right dose of medication for chemotherapy treatment uses a process of trial and error which can cause unnecessary suffering for patients. Adverse effects from taking the wrong dose of medication results in an estimated 280,000 hospitalizations in the US every year, according to the report.

To discover the correct dosage, the team used the "Random Forest Classifier" method, an algorithm which combines the results of decision trees based on slightly different subsets of data. To train the algorithm, the researchers fed it digital information on patients who needed to have their dosages changed from various sources, including analysis results, notes and prescriptions.

"The result of their research illustrates the role that machine learning can play in the initial dosage of drugs associated with a variable response and shows how the health system can gain from being computerized," read theNature Scientific Reports report.

Each year, about 650,000 cancer patients receive chemotherapy treatment in the US, according to the Centers for Disease Control and Prevention. Using AI technology may dramatically improve outcomes and quality of life for patients undergoing treatment.

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