001451695 000__ 04388cam\a2200517\i\4500
001451695 001__ 1451695
001451695 003__ OCoLC
001451695 005__ 20230310004713.0
001451695 006__ m\\\\\o\\d\\\\\\\\
001451695 007__ cr\cn\nnnunnun
001451695 008__ 221206s2022\\\\sz\\\\\\ob\\\\001\0\eng\d
001451695 019__ $$a1351450071$$a1351747577$$a1353231006$$a1354567896
001451695 020__ $$a9783031195020$$q(electronic bk.)
001451695 020__ $$a3031195027$$q(electronic bk.)
001451695 020__ $$z3031195019
001451695 020__ $$z9783031195013
001451695 0247_ $$a10.1007/978-3-031-19502-0$$2doi
001451695 035__ $$aSP(OCoLC)1353300260
001451695 040__ $$aGW5XE$$beng$$erda$$epn$$cGW5XE$$dYDX$$dEBLCP$$dSTF$$dUKAHL$$dOCLCQ
001451695 049__ $$aISEA
001451695 050_4 $$aR859.7.A78
001451695 08204 $$a610.285631$$223/eng/20221206
001451695 1001_ $$aBorhani, Reza,$$eauthor.
001451695 24510 $$aFundamentals of machine learning and deep learning in medicine /$$cReza Borhani, Soheila Borhani, Aggelos K. Katsaggelos.
001451695 264_1 $$aCham, Switzerland :$$bSpringer,$$c2022.
001451695 300__ $$a1 online resource :$$billustrations (color).
001451695 336__ $$atext$$btxt$$2rdacontent
001451695 337__ $$acomputer$$bc$$2rdamedia
001451695 338__ $$aonline resource$$bcr$$2rdacarrier
001451695 504__ $$aIncludes bibliographical references and index.
001451695 5050_ $$aIntroduction -- Mathematical Modeling of Medical Data -- Linear Learning -- Nonlinear Learning -- Multi-Layer Perceptrons -- Convolutional Neural Networks -- Recurrent Neural Networks -- Autoencoders -- Generative Adversarial Networks -- Reinforcement Learning.
001451695 506__ $$aAccess limited to authorized users.
001451695 520__ $$aThis book provides an accessible introduction to the foundations of machine learning and deep learning in medicine for medical students, researchers, and professionals who are not necessarily initiated in advanced mathematics but yearn for a better understanding of this disruptive technology and its impact on medicine. Once an esoteric subject known to few outside of computer science and engineering departments, today artificial intelligence (AI) is a widely popular technology used by scholars from all across the academic universe. In particular, recent years have seen a great deal of interest in the AI subfields of machine learning and deep learning from researchers in medicine and life sciences, evidenced by the rapid growth in the number of articles published on the topic in peer-reviewed medical journals over the last decade. The demand for high-quality educational resources in this area has never been greater than it is today, and will only continue to grow at a rapid pace. Expert authors remove the veil of unnecessary complexity that often surrounds machine learning and deep learning by employing a narrative style that emphasizes intuition in place of abstract mathematical formalisms, allowing them to strike a delicate balance between practicality and theoretical rigor in service of facilitating the readers learning experience. Topics covered in the book include: mathematical encoding of medical data, linear regression and classification, nonlinear feature engineering, deep learning, convolutional and recurrent neural networks, and reinforcement learning. Each chapter ends with a collection of exercises for readers to practice and test their knowledge. This is an ideal introduction for medical students, professionals, and researchers interested in learning more about machine learning and deep learning. Readers who have taken at least one introductory mathematics course at the undergraduate-level (e.g., biostatistics or calculus) will be well-equipped to use this book without needing any additional prerequisites.
001451695 588__ $$aDescription based on print version record.
001451695 650_0 $$aMachine learning$$xTherapeutic use.
001451695 650_0 $$aDeep learning (Machine learning)$$xTherapeutic use.
001451695 655_0 $$aElectronic books.
001451695 7001_ $$aBorhani, Soheila,$$eauthor.
001451695 7001_ $$aKatsaggelos, Aggelos Konstantinos,$$d1956-$$eauthor.
001451695 77608 $$iPrint version:$$aBORHANI, SOHEILA. BORHANI, REZA. KATSAGGELOS, AGGELOS K.$$tFUNDAMENTALS OF MACHINE LEARNING AND DEEP LEARNING IN MEDICINE.$$d[Place of publication not identified] : SPRINGER INTERNATIONAL PU, 2022$$z3031195019$$w(OCoLC)1346070152
001451695 852__ $$bebk
001451695 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-19502-0$$zOnline Access$$91397441.1
001451695 909CO $$ooai:library.usi.edu:1451695$$pGLOBAL_SET
001451695 980__ $$aBIB
001451695 980__ $$aEBOOK
001451695 982__ $$aEbook
001451695 983__ $$aOnline
001451695 994__ $$a92$$bISE