Anna Lee, Gavin M Joynt, Anthony M H Ho, Sheri Keitz, Thomas McGinn, Peter C Wyer
Tips for teachers of evidence-based medicine: making sense of decision analysis using a decision tree
Journal of general internal medicine
kidney pathophysiology often complex nonlinear heterogeneous limits utility hypotheticaldeductive reasoning linear statistical approaches diagnosis treatment emerging evidence suggests artificial intelligence aienabled decision support systems use algorithms based learned examples may important role nephrology contemporary ai applications accurately predict onset acute kidney injury notable biochemical changes occur identify modifiable risk factors chronic kidney disease onset progression match exceed human accuracy recognizing renal tumours imaging studies may augment prognostication decisionmaking following renal transplantation future ai applications potential make realtime continuous recommendations discrete actions yield greatest probability achieving optimal kidney health outcomes realizing clinical integration ai applications require cooperative multidisciplinary commitment ensure algorithm fairness overcome barriers clinical implementation build aicompetent workforce aienabled decision support preserve preeminence wisdom augment rather replace human decisionmaking anchoring intuition objective predictions classifications approach favour clinician intuition honed experience