03358oam 2200481I 450 991080743930332120230822234355.01-000-76672-10-429-34515-110.1201/9780429345159(CKB)4100000011241796(MiAaPQ)EBC6192129(OCoLC)1155202718(OCoLC)1155638023(OCoLC-P)1155202718(FlBoTFG)9780429345159(EXLCZ)99410000001124179620200522h20202020 uy 0engurcnu|||unuuutxtrdacontentcrdamediacrrdacarrierArtificial intelligence for drug development, precision medicine, and healthcare /Mark ChangBoca Raton, FL :CRC Press,[2020]©20201 online resource (xv, 355 pages) illustrationsChapman & Hall/CRC biostatistics series"A Chapman & Hall book".0-367-36292-9 Includes bibliographical references and index.1. Overview of Modern Artificial Intelligence. 2. Classic Statistics and Modern Machine Learning. 3. Similarity Principle- Fundamental Principle of All Sciences. 4. Similarity-Principle-Based Artificial Intelligence. 5. Artificial Neural Network. 6. Deep Learning Neural Network. 7. Kernel Methods. 8. Decision Tree and Ensemble Methods. 9. Bayesian Learning Approach. 10. Unsupervised Learning. 11. Reinforcement Learning. 12.Swarm and Evolutionary Intelligence. 13. Applications of AI in Medical Science and Drug Development. 14. Future Perspectives-Artificial General Intelligence.Artificial Intelligence for Drug Development, Precision Medicine, and Healthcare covers exciting developments at the intersection of computer science and statistics. While much of machine-learning is statistics-based, achievements in deep learning for image and language processing rely on computer sciences use of big data. Aimed at those with a statistical background who want to use their strengths in pursuing AI research, the book: Covers broad AI topics in drug development, precision medicine, and healthcare. Elaborates on supervised, unsupervised, reinforcement, and evolutionary learning methods. Introduces the similarity principle and related AI methods for both big and small data problems. Offers a balance of statistical and algorithm-based approaches to AI. Provides examples and real-world applications with hands-on R code. Suggests the path forward for AI in medicine and artificial general intelligence. As well as covering the history of AI and the innovative ideas, methodologies and software implementation of the field, the book offers a comprehensive review of AI applications in medical sciences. In addition, readers will benefit from hands on exercises, with included R code.Chapman & Hall/CRC biostatistics series.Artificial intelligenceMedical applicationsArtificial intelligenceMedical applications.610.28563Chang Mark520702OCoLC-POCoLC-PBOOK9910807439303321Artificial intelligence for drug development, precision medicine, and healthcare4120702UNINA