Chapter Contents: Abstract 17.1 Introduction 17.1.1 Steps to build a machine learning model 17.1.2 Machine learning terminology 17.1.3 ML algorithms 17.2 Literature review 17.2.1 Applications of machine learning in healthcare 17.3 Disease identification and diagnosis 17.3.1 Heart disease 17.3.2 Diabetes 17.3.3 Liver disease 17.3.4 Dengue disease 17.3.5 Hepatitis disease 17.4 Drug discovery and manufacturing 17.5 Electronic health records 17.6 Disease prediction using machine learning 17.7 Fairness 17.7.1 Fairness in the dataset 17.7.2 Fairness in model or algorithm 17.7.3 Fairness in the metrics/results 17.8 Data analytics role in healthcare 17.8.1 Predictive modeling 17.8.2 Reduction in healthcare costs 17.8.3 Empowering advanced chronic disease prevention 17.9 Deep learning applications in healthcare 17.9.1 Drug discovery 17.9.2 Challenges faced by deep learning applications in healthcare 17.10 Conclusion and future scope References
Authors: Manas Kumar Yogi, Jyotsna Garikipati, Jyotir Moy Chatterjee
DOI: https://doi.org/10.1049/pbhe038e_ch17
Publish Year: 2022
