Application of Deep Learning Methods in Healthcare and Medical Science
Tanwar, Rohit, Kumar, Prashant, Kumar, Malay
This volume provides a wealth of up-to-date information on developments and applications of deep learning in healthcare and medicine. It aims to provide deep insight and understanding of novel applications that address the tough questions of disease diagnosis, prevention, and immunization. The volume looks at applications of deep learning for major medical challenges such as cancer detection and identification, birth asphyxia among neonates, kidney abnormalities, white blood cell segmentation, diabetic retinopathy detection, and Covid-19 diagnosis, prevention, and immunization. The volume discusses applications of deep learning in detection, diagnosis, intensive examination and evaluation, genomic sequencing, convolutional neural networks for image recognition and processing, and more for health issues such as kidney problems, brain tumors, lung damage, and breast cancer. The authors look at ML for brain tumor segmentation, in lung CT scans, in digital X-Ray devices, and for a logistic and transport systems for effective delivery of healthcare.
Chapters include studies and discussions on chest X-ray images using CNN to identify Covid-19 infections, lung CT scan images using pre-trained VGG-16 and 3-layer CNN to distinguish Covid and non-Covid patients, genomic sequencing to study the Covid virus, breast cancer identification using CNN, brain tumor detection using multimodal image fusion and segmentation, factors responsible for birth asphyxia in neonates, and much more. It also explores cancer identification and detection using deep learning methods in the human body through algorithms based on issues, laboratory tests, imaging tests, biopsies, bone scans, computerized tomography scans, positron emission tomography, and ultrasound.
This volume, Application of Deep Learning Methods in Healthcare and Medical Science, showcases the diverse applications of patient-based data collection and analysis in medicine and healthcare using computer algorithms for effective health diagnosis, prevention, and patient care.
Rohit Tanwar, PhD, is Associate Professor at the School of Computer Sciences, University of Petroleum and Energy Studies, Dehradun, India. He has more than 10 years of experience in teaching. His areas of interests include network security, optimization techniques, human computing, soft computing, cloud computing, data mining, etc. Dr. Tanwar has published one book and has several others in progress. He is associated with several international journals as guest editor and reviewer. He has more than 30 publications to his credit to date in reputed journals and conferences.
Prashant Kumar, PhD, is Assistant Professor in the Department of Computer Science and Engineering at the Dr. BR Ambedkar National Institute of Technology, Jalandhar, India. Previously he has worked with the Department of Systemics in the School of Computer Science at the University of Petroleum and Energy Studies, Dehradun, India, and the Department of Computer Science and Engineering at the National Institute of Technology Hamirpur, India. He has published more than 25 research papers.
Malay Kumar, PhD, is Assistant Professor in the Department of Computer Science and Engineering at the Indian Institute of Information Technology Dharwad, India. Earlier he was associated with the School of Computer Science of the University of Petroleum and Energy Studies, Dehradun, India. He has authored more than 20 research papers in international journals and conferences. He has served as chair and technical program committee member for international conferences and workshops and was a guest editor of several international journals.
Neha Nandal, PhD, is Associate Professor in the Computer Science and Engineering Department of the Gokaraju Rangaraju Institute of Engineering and Technology, Hyderabad, India. She has published 19 articles in her research area in different journals and conferences. Dr. Nandal has participated in workshops; completed courses on Python, machine learning, and deep learning on Coursera; and also hosted several faculty development programs.
Prashant Kumar博士是印度賈蘭達爾Dr. BR Ambedkar國家技術研究所計算機科學與工程系的助理教授。他曾在印度德拉敦石油和能源研究大學計算機科學學院的系統學系以及印度哈密爾普爾國家技術研究所計算機科學與工程系工作。他已經發表了25多篇研究論文。
Neha Nandal博士是印度海得拉巴Gokaraju Rangaraju工程技術學院計算機科學與工程系的副教授。她在不同期刊和會議上發表了19篇研究論文。Nandal博士參加了工作坊，完成了Coursera上的Python、機器學習和深度學習課程，並主持了幾個教師發展計劃。