Cognitive Learning Approach to Enrich Understanding of Machine Learning on Healthcare Data

Machine Learning (ML) has a significant impact on applications across various disciplines, with a key requirement of domain knowledge. A fully guided cognitive framework is presented in the case study for medical data analysis using the ML approach with an influence of the feature extraction effect, ensemble methods, and voting classifier using hyperparameter tuning. A case study-driven guided project design technique helps the student to comprehend the subject better. The learner gets familiar with reliable data sources and associated analysis jargon. The student is familiar with different intermediate steps, process flow, and legitimate conclusion dragging. The result shows that confidence in capstone project design in the relevant field and handling medical data is developed in learners. The learning removes hesitation of interdisciplinary work in the cognitive classroom. This strategy can successfully drive lifelong learning for all emerging computer science courses.