• Dominant cognitive patterns in clinical decision making under uncertainty emerged as researchers compared 'thinking aloud' reasoning with formal decision analysis, revealing sequential, experience-influenced judgments and systematic probability estimation biases [1], [2], [11], [14].

• Early computer-based decision support and knowledge bases integrated into care, with expert systems, the HELP clinical information system, desktop knowledge resources, and structured admission classifications to capture and present clinical knowledge [17], [9], [8], [16], [18].

• Quantitative decision support targeted prognosis and resource allocation, exemplified by hospital-mortality risk models, cost-effectiveness simulations, and explicit balance of benefits and harms to guide policy and practice [10], [5], [7].

• Evaluation and methodological foundations for CDS, including error estimation, expert-panel decision making, and evaluation of decision-support alerts, aimed at establishing generalizability and performance in real-world settings [12], [20], [6].