Drug Discovery and Telemedicine
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分類:英文書>自然科普>其他電腦資訊追蹤? 追蹤分類後,您會在第一時間收到分類新品通知。
- 作者: Saurav,Mallik 追蹤 ? 追蹤作者後,您會在第一時間收到作者新書通知。
- 出版社: de Gruyter 追蹤 ? 追蹤出版社後,您會在第一時間收到出版社新書通知。
- 出版日:2025/03/30
內容簡介
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
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