Accuracy of an Artificial Intelligence System for Cancer Clinical Trial Eligibility Screening: Retrospective Pilot Study.
Tufia C HaddadJane M HelgesonKatharine E PomerleauAnita M PreiningerM Christopher RoebuckIrene Dankwa-MullanGretchen Purcell JacksonMatthew P GoetzPublished in: JMIR medical informatics (2021)
The AI CDSS in this study demonstrated accuracy, sensitivity, and specificity of greater than 80% in determining the eligibility of patients for breast cancer clinical trials. CDSSs can accurately exclude ineligible patients for clinical trials and offer the potential to increase screening efficiency and accuracy. Additional research is needed to explore whether increased efficiency in screening and trial matching translates to improvements in trial enrollment, accruals, feasibility assessments, and cost.
Keyphrases
- clinical trial
- artificial intelligence
- phase ii
- end stage renal disease
- newly diagnosed
- phase iii
- study protocol
- ejection fraction
- machine learning
- chronic kidney disease
- healthcare
- prognostic factors
- risk assessment
- open label
- squamous cell carcinoma
- deep learning
- big data
- double blind
- patient reported outcomes
- human health
- climate change
- lymph node metastasis