Handbook of AI-Based Models in Healthcare and Medicine: Approaches, Theories, and Applications

本手冊提供了人工智慧（AI）、機器學習（ML）、深度學習（DL）、自然語言處理（NLP）、密碼學和區塊鏈等方法的全面、深入和重點發展，並聚焦於醫療保健系統的應用。

《基於人工智慧模型的醫療保健與醫學手冊：方法、理論和應用》從實踐和理論的角度，突出了智能系統在醫療領域的不同方法、理論和應用。它在討論人類生物學、醫療保健和醫學時採用了醫學導向的方法，並呈現了基於NLP的醫學報告和醫學增強。該手冊包括了用於醫療保健系統管理的ML和DL的先進模型，並討論了基於區塊鏈的醫療保健管理。此外，手冊還提供了AI、ML和DL在解決醫療保健問題上的應用案例。

對於對ML/DL在醫療保健環境中的應用感興趣的本科生、研究生、學者、研究人員和業界專業人士來說，這本參考書是必備的。

Dr. Bhanu Chander, working as Assistant Professor at Indian Institute of Information Technology (IIIT-K), Pala, Kerala, India, graduated from Acharya Nagarjuna University, Andhra Pradesh, India, and received a postgraduate degree from the Central University of Rajasthan, India. Dr. Bhanu earned a Ph.D. in Machine Learning in Wireless Sensor Networks for Sensor Data Classification from Pondicherry University, India, in 2022. Dr. Bhanu's primary research interests are in the areas of wireless sensor networks, machine learning, and IoT security. As we know, computer science as a field has largely focused on problems relevant to the developed world. The internet and the world wide web have remained largely urban phenomena, which means that a significant fraction of the developing world, especially in rural and underdeveloped regions, remains disconnected from the rest of the world. Dr. Bhanu is an academic reviewer recognized by IEEE, ACM, and Springer, and has served for 16 various scientific journals and conferences in the review process of more than 50 articles. He contributed as a track chair and session chair for numerous international conferences and workshops, and performed as a technical program committee (TPC) member for several international conferences organized by IEEE, Springer, and ACM.

He is interested in machine learning techniques for energy-efficient 6G networks, blockchain technology for the security of the Internet of Things and wireless communications, analysis and verification of cryptographic protocols, and identification of novel features or misclassified features in satellite image analysis. He published eight articles in peer-reviewed journals, five international conferences, and eight book chapters (Elsevier, Wiley, CRC, and Springer). Presently, his main areas of interest include wireless sensor networks (WSN), IoT and healthcare, cryptography, machine learning, and deep learning.

Dr. Anoop, working as Postdoctoral Research Fellow at Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Centre, US, received a Ph.D. degree in the Development of Automated Methods for Retinal Optical Coherence Tomography Image Analysis from the National Institute of Technology, Surathkal, India, in 2021 and M.Tech on Signal Processing from National Institute of Technology, Calicut, India, 2013. He received the Best Paper award at the ninth International Conference on Pattern Recognition and Machine Intelligence, PReMI 2021 for the work entitled "Attention-Assisted Patchwise CNN for the Segmentation of Fluids from the Retinal Optical Coherence Tomography Images" Organized by Machine Intelligence Unit, Indian Statistical Institute (ISI), Kolkata, India, in December 2021. He attended the 43rd-annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC21). Research fellow on a project entitled "Retinal Cysts Identification and Quantification from Low-SNR Optical Coherence Tomography Scans Using Image Processing Techniques" (funding agency: DST-SERB) from May 2017 to March 2020. He has membership in the professional bodies IEEE, IEEE Signal Processing, Engineering in Medicine and Biology Society, and Internet Society.

He published six articles in peer-reviewed journals and two book chapters. Presently, his main areas of interest include medical image processing, deep learning, GANs and auto-encoders.

Dr. Koppala Guravaiah, working as Assistant Professor at Indian Institute of Information Technology (IIIT-K), Pala, Kerala, India, completed a Ph.D. on the topic of Performance of Routing Protocols in Wireless Sensor Networks using River Formation Dynamics from National Institute of Technology Tiruchirappalli, India. His research interests include the Internet of Things (IoT), wireless sensor networks, MANETs, applications and security aspects in IoT, WSN, and MANETs, and natural language processing. He is an active speaker at various international and national conferences. He contributed as a track chair and session chair for numerous international conferences and workshops and pe0rformed as a technical program committee member for several international conferences. He has published in five journals, eight conferences, and contributed two book chapters in the areas mentioned above. He is a member of various professional research bodies, such as IEEE and ACM.

Dr. G. Kumaravelan currently serves as Associate Professor at Department of Computer Science, School of Engineering and Technology, Pondicherry University, Karaikal Campus, Karaikal, India. He received his M.Tech in Advanced Information Technology and his Ph.D. in Computer Science from Bharathidasan University, Trichy, India, in 2009 and 2013, respectively. He has published more than 25 research papers in reputed international journals indexed in Scopus and SCI and conferences including IEEE, SPRINGER, and ACM. He received two best paper awards in the international conferences organized by the IITs. He has received "Best Teacher Award" from Pondicherry University, based on students' evaluation, for the past six years (2013-14, 2014-15, 2015-16, 2016-17, 2017-18, and 2018-19). He has gained 17 years of rich teaching and research experience. He is an active reviewer in various international conferences and peer-reviewed journals, and has reviewed more than 200 papers. He has acted as a resource person in various FDPs, conferences, and seminars in higher educational institutions. He contributed as a track chair and session chair for numerous international conferences and workshops and performed as a TPC member for several international conferences. His research interests include the Internet of Things, cloud computing, big data analytics, wireless communications, and networking.

Dr. Bhanu Chander博士，現任印度信息技術學院（IIIT-K）的助理教授，位於印度喀拉拉邦帕拉，畢業於安得拉邦的阿查亞·納加魯納大學，並在印度拉賈斯坦中央大學獲得碩士學位。Dr. Bhanu於2022年在印度本地治里大學獲得機器學習在無線傳感器網絡中的傳感器數據分類方面的博士學位。Dr. Bhanu的主要研究興趣包括無線傳感器網絡、機器學習和物聯網安全。正如我們所知，計算機科學作為一個領域主要關注的是發達國家的問題。互聯網和世界各地的網絡主要是城市現象，這意味著發展中世界的相當一部分，特別是在農村和不發達地區，仍然與世界其他地區脫節。Dr. Bhanu是IEEE、ACM和Springer認可的學術審稿人，曾在16個不同的科學期刊和會議上擔任審稿人，審查了50多篇文章。他曾擔任多個國際會議和研討會的軌道主席和會議主席，並擔任IEEE、Springer和ACM組織的多個國際會議的技術計劃委員會（TPC）成員。

他對能源高效的6G網絡的機器學習技術、區塊鏈技術用於物聯網和無線通信的安全、加密協議的分析和驗證以及衛星圖像分析中新特徵或分類錯誤特徵的識別感興趣。他在同行評審的期刊上發表了八篇文章，五篇國際會議論文和八篇專書章節（Elsevier、Wiley、CRC和Springer）。目前，他的主要研究領域包括無線傳感器網絡（WSN）、物聯網和醫療保健、加密學、機器學習和深度學習。

Dr. Anoop博士，現任德克薩斯健康科學中心格倫·比格斯阿爾茨海默病和神經退行性疾病研究所的博士後研究員，於2021年在印度Surathkal的國家技術研究所獲得了關於視網膜光學相干斷層掃描圖像分析的自動化方法的博士學位，並於2013年在印度Calicut的國家技術研究所獲得了信號處理的碩士學位。他在2021年第九屆國際模式識別和機器智能會議（PReMI 2021）上以“基於注意力輔助的區塊CNN對視網膜光學相干斷層掃描圖像中液體的分割”獲得了最佳論文獎，該會議由印度統計研究所（ISI）的機器智能單位於2021年12月在印度加爾各答舉辦。他參加了第43屆IEEE工程醫學和生物學協會（EMBC21）國際會議。他在2017年5月至2020年3月期間擔任了一個名為“使用圖像處理技術從低信噪比光學相干斷層掃描中識別和量化視網膜囊腫”的項目的研究員（資助機構：DST-SERB）。他是IEEE、IEEE信號處理、工程醫學和生物學協會以及互聯網協會的會員。

他在同行評審的期刊上發表了六篇文章和兩篇專書章節。目前，他的主要研究領域包括醫學圖像處理、深度學習、生成對抗網絡（GANs）和自編碼器。

Dr. Koppala Guravaiah博士，現任印度信息技術學院（IIIT-K）的助理教授，從印度Tiruchirappalli的國家技術研究所獲得了關於無線傳感器網絡中路由協議性能的研究，使用了河流形成動力學的博士學位。他的研究興趣包括物聯網（IoT）、無線傳感器網絡、MANETs、IoT、WSN和MANETs中的應用和安全方面。