Application of Deep Learning Methods in Healthcare and Medical Science

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.

本書提供了關於深度學習在醫療保健和醫學領域發展和應用的豐富最新資訊。它旨在提供對解決疾病診斷、預防和免疫等重要問題的新應用的深入洞察和理解。本書探討了深度學習在重大醫學挑戰（如癌症檢測和識別、新生兒窒息、腎臟異常、白血球分割、糖尿病視網膜病變檢測以及Covid-19的診斷、預防和免疫）中的應用。本書還討論了深度學習在檢測、診斷、密集檢查和評估、基因組序列、卷積神經網絡用於圖像識別和處理等方面的應用，以及對腎臟問題、腦腫瘤、肺損傷和乳腺癌等健康問題的應用。作者們還研究了腦腫瘤分割、肺部CT掃描、數字X射線設備以及物流和運輸系統等方面的應用，以實現有效的醫療保健交付。

各章節包括使用卷積神經網絡（CNN）對胸部X射線圖像進行研究和討論，以識別Covid-19感染，使用預訓練的VGG-16和3層CNN區分Covid和非Covid患者的肺部CT掃描圖像，使用基因組序列研究Covid病毒，使用CNN進行乳腺癌識別，使用多模態圖像融合和分割進行腦腫瘤檢測，研究新生兒窒息的原因等等。本書還探討了在人體中使用深度學習方法進行癌症識別和檢測的問題，包括基於問題、實驗室檢測、影像檢測、活體檢查、骨骼掃描、電腦斷層掃描、正子發射斷層掃描和超聲波的算法。

本書《深度學習方法在醫療保健和醫學科學中的應用》展示了使用計算機算法進行有效的健康診斷、預防和患者護理的基於患者數據收集和分析的多樣應用。

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.

Rohit Tanwar博士是印度德拉敦石油和能源研究大學計算機科學學院的副教授。他在教學方面擁有超過10年的經驗。他的研究興趣包括網絡安全、優化技術、人類計算、軟計算、雲計算、數據挖掘等。Tanwar博士已經出版了一本書，並有幾本正在進行中。他是幾個國際期刊的客座編輯和審稿人。迄今為止，他在知名期刊和會議上已經發表了30多篇論文。

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。

Malay Kumar博士是印度達爾瓦德印度信息技術學院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工作。他在國際期刊和會議上發表了20多篇研究論文。他曾擔任國際會議和研討會的主席和技術計劃委員會成員，並擔任幾個國際期刊的客座編輯。

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。