Drug Discovery and Telemedicine : Through Artificial Intelligence, Computer Vision, and IoT
Language: English
Published by De Gruyter, 2025
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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US$ 154.55
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Neuware - Our proposed book emerges in response to the critical need for an interdisciplinary resource that encapsulates the burgeoning role of artificial intelligence (AI) in reshaping drug discovery and telemedicine. As these sectors witness transformative changes driven by AI technologies, there's a pressing demand for a comprehensive guide that navigates through these advancements, offering insights, methodologies, and practical applications to professionals at the forefront of healthcare and pharmaceutical research. At its core, the book delves into the intricate ways in which AI and machine learning algorithms are being harnessed to streamline the drug development process, from initial discovery through to clinical trials, and how these technologies are concurrently revolutionizing the delivery of healthcare services via telemedicine. Specific focus areas include the application of deep learning in identifying novel drug candidates, AI-driven predictive models for pharmacokinetics and pharmacodynamics, automation in laboratory research, and the integration of AI in diagnostic processes, personalized medicine, and patient monitoring systems. Each chapter not only explores current state-of-the-art methodologies and case studies but also critically examines challenges, such as data privacy, ethical considerations, and the need for robust, interpretable models that can be trusted by healthcare professionals and patients alike. Furthermore, the book places a strong emphasis on the synergistic potential of combining AI with telemedicine, illustrating how these technologies can expand access to healthcare, improve the accuracy of remote diagnoses, and enable continuous, data-driven patient care. By providing a panoramic view of current trends, technological innovations, and future directions, the book aims to serve as a pivotal reference for scientists, researchers, clinicians, and policymakers involved in drug discovery and healthcare delivery. In conclusion, this book stands as an essential compendium for specialists seeking to navigate the complexities and harness the opportunities presented by AI in the pharmaceutical and healthcare industries. It offers a critical, in-depth exploration of the transformative impact of AI technologies, underscoring their relevance and potential to dramatically enhance drug discovery and telemedicine practices. This publication not only equips its target audience with the knowledge to lead innovation in their fields but also engages with the broader ethical, social, and practical implications of AI, making it an invaluable resource for advancing towards more effective, efficient, and accessible healthcare solutions. The book is significant for several reasons: Interdisciplinary Appeal: It serves as a critical resource for professionals and researchers across the fields of computer science, pharmaceutical sciences, and healthcare, facilitating a deeper understanding of AI's potential and fostering interdisciplinary collaborations. Innovation in Drug Discovery: By highlighting novel AI methodologies in drug discovery, the book offers insights into how these technologies can shorten the development timelines, reduce costs, and increase the success rates of new therapies, which is crucial for addressing unmet medical needs. Revolutionizing Telemedicine: The detailed discussion on AI's role in telemedicine illustrates how these advancements can enhance access to healthcare, improve the quality of care, and make healthcare systems more efficient, especially in remote and underserved areas. Ethical and Regulatory Considerations: It likely addresses the ethical, privacy, and regulatory challenges associated with implementing AI in healthcare, offering guidelines for navigating these complexities while maximizing patient benefits. Future Directions: By e.…
Seller Inventory # 9783111503981
- Title
- Drug Discovery and Telemedicine : Through Artificial Intelligence, Computer Vision, and IoT
- Author
- Saurav Mallik
- Publisher
- De Gruyter
- Publication year
- 2025
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 3111503984
- ISBN 13
- 9783111503981
- Item weight
- 491 grams
- Dimensions
- 242x170x15 mm
Our proposed book emerges in response to the critical need for an interdisciplinary resource that encapsulates the burgeoning role of artificial intelligence (AI) in reshaping drug discovery and telemedicine. As these sectors witness transformative changes driven by AI technologies, there's a pressing demand for a comprehensive guide that navigates through these advancements, offering insights, methodologies, and practical applications to professionals at the forefront of healthcare and pharmaceutical research.
At its core, the book delves into the intricate ways in which AI and machine learning algorithms are being harnessed to streamline the drug development process, from initial discovery through to clinical trials, and how these technologies are concurrently revolutionizing the delivery of healthcare services via telemedicine. Specific focus areas include the application of deep learning in identifying novel drug candidates, AI-driven predictive models for pharmacokinetics and pharmacodynamics, automation in laboratory research, and the integration of AI in diagnostic processes, personalized medicine, and patient monitoring systems. Each chapter not only explores current state-of-the-art methodologies and case studies but also critically examines challenges, such as data privacy, ethical considerations, and the need for robust, interpretable models that can be trusted by healthcare professionals and patients alike.
Furthermore, the book places a strong emphasis on the synergistic potential of combining AI with telemedicine, illustrating how these technologies can expand access to healthcare, improve the accuracy of remote diagnoses, and enable continuous, data-driven patient care. By providing a panoramic view of current trends, technological innovations, and future directions, the book aims to serve as a pivotal reference for scientists, researchers, clinicians, and policymakers involved in drug discovery and healthcare delivery.
In conclusion, this book stands as an essential compendium for specialists seeking to navigate the complexities and harness the opportunities presented by AI in the pharmaceutical and healthcare industries. It offers a critical, in-depth exploration of the transformative impact of AI technologies, underscoring their relevance and potential to dramatically enhance drug discovery and telemedicine practices. This publication not only equips its target audience with the knowledge to lead innovation in their fields but also engages with the broader ethical, social, and practical implications of AI, making it an invaluable resource for advancing towards more effective, efficient, and accessible healthcare solutions.
The book is significant for several reasons:
Interdisciplinary Appeal: It serves as a critical resource for professionals and researchers across the fields of computer science, pharmaceutical sciences, and healthcare, facilitating a deeper understanding of AI's potential and fostering interdisciplinary collaborations.
Innovation in Drug Discovery: By highlighting novel AI methodologies in drug discovery, the book offers insights into how these technologies can shorten the development timelines, reduce costs, and increase the success rates of new therapies, which is crucial for addressing unmet medical needs.
Revolutionizing Telemedicine: The detailed discussion on AI's role in telemedicine illustrates how these advancements can enhance access to healthcare, improve the quality of care, and make healthcare systems more efficient, especially in remote and underserved areas.
Ethical and Regulatory Considerations: It likely addresses the ethical, privacy, and regulatory challenges associated with implementing AI in healthcare, offering guidelines for navigating these complexities while maximizing patient benefits.
Future Directions: By exploring current trends and future possibilities, the book not only serves as a repository of current knowledge but also as a beacon for future research and development efforts in these rapidly evolving fields.
"Synopsis" may belong to another edition of this title.
About the Author
Dr. Saurav Mallik, PhD (Engg.), Member, IEEE, AACR, ACM, BioClues is currently working as Research Scientist in the Department of Pharmacology and Toxicology, The University of Arizona, USA. Previously, he worked as Postdoctoral Fellow in Harvard T.H. Chan School of Public Health, Boston, MA, USA for more than three years (2019-2022), the Center of Precision Health, Department of School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, Texas, USA for one and half year (2018-2019), and in the Division of Bio-statistics, Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, Florida, USA for more than one year (2017-2018). He obtained his PhD degree in the Department of Computer Science and Engineering (C.S.E.) from Jadavpur University, Kolkata, India in 2017 while his PhD works carried out in Machine Intelligence Unit, Indian Statistical Institute, Kolkata, India as Junior Research Fellow and Visiting Scientist. He has obtained the award of Research Associateship from CSIR (Council of Scientific and Industrial Research), MHRD, Govt. of India in 2017. Dr. Mallik has more than 150 research papers in different top high impact factor peer-reviewed International Journals, Conferences and Book Chapters. He published several Books and Patents. He is working as the active member of Institute of Electrical and Electronics Engineers (IEEE), USA, ACM and American Association for Cancer Research (AACR), USA and Bioclues, India. He has also worked with section editors and reviewers with several well-reputed high impact journals. His research interest includes Computational Biology, Knowledge Retrieval and Data Mining, Bioinformatics, Bio-Statistics and Machine Learning/Deep Learning.
Dr. Zubair Rahaman, Member,AMA, ACP, MCI, Sigma Xi is an Associate Professor, UCF Internal Medicine Orlando, FL (December 2023 - Present) and Associate Medical Director Physician Vitas Healthcare, Kissimmee, FL (August 2022 - Present). He has completed his M.B.B.S. (Bachelor of Medicine & Bachelor of Surgery) from Vijayanagara Institute of Medical Sciences, Bellary, India. He has professional memberships of American Medical Association (AMA), American College of Physicians (ACP), Medical Council of India (MCI), Gold Humanism Honor Society, Sigma Xi Scientific Research Honor Society. He encompasses a wide array of clinical investigations and academic contributions. His roles have involved managing clinical trials, coordinating Institutional Review Board (IRB) submissions, and spearheading geriatric research initiatives.
Dr. Soumita Seth, PhD (Engg.) is currently serving as an Assistant Professor in the Department of Computer Science and Engineering of Future Institute of Engineering and Management, Kolkata, India, Affiliated to MAKAUT, Kolkata. Besides, she is recently submitted her PhD thesis in the Department of Computer Science & Engineering (CSE) from a state-government university, Aliah University (AU), Kolkata, India. Previously, She completed M.Tech. and B.Tech. from the departments of CSE and IT, respectively. She is also collaborating her PhD research with The University of Texas Health Science Center at Houston (UTHealth), Houston, TX 77030, USA. She has Academic Experience of almost 7 years, Fulltime Research Experience of 2 years, and Industrial Experience of 2 years. Dr. Seth has more than 10 research papers in different top high impact factor peer-reviewed International Journals, Conferences and Book Chapters. She has also worked with section editors and section reviewers with several well-reputed high impact journals. Her research interests include Computational Biology, Data Mining, Bioinformatics, Pattern Recognition, Biological Regulatory Networks, Biostatistics, Machine learning/Deep learning.
Dr. Anjan Bandyopadhyay, PhD (Engg.) is an Assistant Professor of Kalinga Institute of Industrial Technology, Bhubaneswar, Odisha , India. He has completed his Ph.D from National Institute of Technology, Durgapur, West Bengal, India in Vishveshwarya Ph.D fellowship under MHRD. He has completed His M.Tech in Information Security from National Institute of Technology, Durgapur, West Bengal, India. He is broadly interested in Algorithmic Game Theory (Mechanism Design). He has published many Journals and Conference papers in esteemed Journal and Conference. His current research interest include Game Theory, Cloud Computing, Metaverse, Virtual Reality, Augmented Reality, Fog Computing, Healthcare, IoT and Machine Learning.He bags number of Best Paper Award from many conferences like 3PGCIC. He is doing many collaborative work with many foreign Universities.
Dr. Sujata Swain, PhD (Engg.) is an Assistant Professor of Kalinga Institute of Industrial Technology, Bhubaneswar, Odisha. She holds a Ph.D. (CSE) and M.Tech (CSE) degree from IIT Roorkee. She has taught Programming in C, Computer Organization and Organization and High Performance Computer Architecture. She has published many Journals and Conference papers in esteemed Journal and Conference. Her research interests are modelling and verification tools, web service composition and pervasive computing.
Dr. Somenath Chakraborty, PhD (Engg.), Member, IEEE is an Assistant Professor at The West Virginia University Institute of Technology, Beckley, West Virginia, USA. He has experience of 11 years at the post of Lecturer, Assistant Professor, and Principal. Former Principal of Harirampur Government ITI, Nanoor Government ITI and Itahar Government ITI. Strong research expertise in the field of Artificial Intelligence, Medical image and Data Processing, Machine learning, Pattern Recognition and Digital Image Processing. He has published many research journals, conference papers, book chapters etc. where he is the first author. He is an IEEE Senior Member, IEEE Computer Society, IEEE Computational Intelligence Society (CIS), IEEE Young Professionals, The IEEE Computer Society Bio-inspired Computing Special Technical Community (STC) etc. He is also Reviewer of Many IEEE, Springer journals, etc. Editor of many journals and Technical and Organizing Committee Member of Many International Conferences. He was the President (2021-2022) and Secretary(2020-2021) of Graduate Student Association for Arts and Sciences (CAS GRADS) at The University of Southern Mississippi. He is passionate about Machine Learning, Data Science, Data Analytics, Pattern recognition, Computer Vision, image processing, Artificial Intelligence, Cloud Computing and Blockchain.
"About the title" may belong to another edition of this title.
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