Full Description
Machine learning is playing an indispensable role in framing clinical decisions and enhancing accuracy. This new book offers a comprehensive take on the field of biomedical and health informatics, discussing topics that include predictive health analytics, pandemic management, AI ethics, application and integration of Internet of Things and machine learning for effective healthcare, and more. The book covers a range of bioinformatics tools and methods and their relation to drug designing and drug screening using ML. Several chapters cover clustering techniques and other methods for analyzing human heart-related disorders. The authors also explore the use of ML in creating adaptive therapies for using chemotherapy and androgen deprivation therapy for prostate cancer and for tracking diseases such as Parkinson's Speech, Covid-19, and others. Case studies are included that demonstrate the practical use of ML in healthcare informatics.
Contents
1. Role of Machine Learning in High-Throughput Screening of Drug Molecules 2. Solving a Capacitated Vehicle Routing Problem with Time Windows Using Dijkstra's Algorithm: A Case Study on COVID Vaccine Distribution 3. Heart Disease Prediction: A Clustering-Based Clinical Decision Support Approach 4. Application of Fuzzy Tools to Avoid Reoccurrence of Prostate Cancer Post-Treatment 5. Machine Learning: A Quantum Leap in Data Mining Modalities for Healthcare Upliftment 6. Impact of Matrix Factorization-Based Dimensionality Reduction in the Prediction of Diseases 7. Applications of Bioinformatics and Machine Learning Algorithms in Survival Analysis of Cancer Patients 8. Speech Signal Analysis Using Gammatone-Frequency Cepstral Coefficient for Parkinson's Disease Prediction 9. Evaluating the Performance of Tree-Based Classifiers for Predicting Marginal and Acute Cardiovascular Diseases: A Comprehensive Review 10. Human Health Data Analysis Using Machine Learning 11. COVIDIncResNet: An Efficient Approach for CNN-Based Covid Classification Model Using ECG Images 12. The Role of Artificial Intelligence in Medical Image Analysis for Disease Diagnosis 13. Application of Machine Learning in Bioinformatics: Capture and Interpret Biological Data
