Machine Learning in Biomedical and Health Informatics (eBook, PDF)
Current Applications and Challenges
Redaktion: Sahana, Sudip Kumar; Chatterjee, Prasenjit; Choudhury, Panchali Datta; Mukherjee, Rajendrani
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Machine Learning in Biomedical and Health Informatics (eBook, PDF)
Current Applications and Challenges
Redaktion: Sahana, Sudip Kumar; Chatterjee, Prasenjit; Choudhury, Panchali Datta; Mukherjee, Rajendrani
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Discusses ML in predictive health analytics, pandemic management, AI ethics, application and integration of IoT and ML for effective healthcare, and more. Covers a range of bioinformatics tools and methods and their relation to drug designing and screening using ML.
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- Größe: 16.74MB
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Discusses ML in predictive health analytics, pandemic management, AI ethics, application and integration of IoT and ML for effective healthcare, and more. Covers a range of bioinformatics tools and methods and their relation to drug designing and screening using ML.
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Produktdetails
- Produktdetails
- Verlag: Taylor & Francis eBooks
- Seitenzahl: 290
- Erscheinungstermin: 23. September 2025
- Englisch
- ISBN-13: 9781040424261
- Artikelnr.: 74390342
- Verlag: Taylor & Francis eBooks
- Seitenzahl: 290
- Erscheinungstermin: 23. September 2025
- Englisch
- ISBN-13: 9781040424261
- Artikelnr.: 74390342
- Herstellerkennzeichnung Die Herstellerinformationen sind derzeit nicht verfügbar.
Sudip Kumar Sahana, PhD, is an Associate Professor of Computer Science and Engineering at the Birla Institute of Technology, Mesra, India. His research and teaching interests include soft computing, computational intelligence, distributed computing, and artificial intelligence. He has authored many articles, research papers, and books and is also an editorial board member and reviewer for several reputed journals. He is also the inventor of five patents in the field of artificial intelligence. He has carried out numerous R&D-sponsored projects of around 1.22 million USD. Rajendrani Mukherjee, PhD, is an Associate Professor of Computer Systems & Information Technology at the Institute of Engineering and Management of the University of Engineering and Management, Kolkata, India. She was formerly affiliated with the Calcutta Institute of Engineering and Management and with multinational corporations such as IBM and Fuzzy Logix. She has published journal and conference research papers and book chapters and served as a conference session chair. Panchali Datta Choudhury, PhD, is an Assistant Professor at the University of Engineering and Management, Kolkata, India, in the Department of Computer Science and Technology. She completed her PhD in Computer Science and Engineering at the National Institute of Technology, Durgapur, India. Her research interest includes optical networking and protection management in optical networks. She is a member of the Optical Society of America and IEEE. Prasenjit Chatterjee, PhD, is Dean (Research and Consultancy) at the MCKV Institute of Engineering, West Bengal, India. He has published over 130 research papers in international journals and peer-reviewed conferences and has authored and edited more than 15 books on intelligent decision-making, supply chain management, optimization techniques, risk, and sustainability modeling. He has received numerous awards for his work. He is editor of several book series.
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
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
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
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