000			02938nmm a2200313 a 4500
005			20230705152853.0
008			210728s2022 nju ob 001 0 eng d
010			_a 2021036691
020			_a9781800610941 _q(ebook)
020			_a1800610947 _q(ebook)
020			_z9781800610934 _q(hbk.)
020			_z1800610939 _q(hbk.)
082			_a610.285 _223
245			_aDeep learning in biology and medicine _h[electronic resource] / _ceditors, Davide Bacciu, Paulo J.G. Lisboa, Alfredo Vellido.
260			_aNew Jersey : _bWorld Scientific, _c2022.
300			_a1 online resource (332 p.)
504			_aIncludes bibliographical references and index.
505			_aIntroduction -- Deep learning for medical imaging -- The evolution of mining electronic health records in the era of deep learning -- Natural language technologies in the biomedical domain -- Metabolically driven latent space learning for gene expression data -- Deep learning in cheminformatics -- Deep learning methods for network biology -- The need for interpretable and explainable deep learning in medicine and healthcare -- Ethical, societal and legal issues in deep learning for healthcare.
520			_a"Biology, medicine and bio-chemistry have become data-centric fields for which Deep Learning methods are delivering ground-breaking results. Addressing high impact challenges, Deep Learning in Biology and Medicine provides an accessible and organic collection of Deep Learning essays on bioinformatics and medicine. It caters for a wide readership, ranging from machine learning practitioners and data scientists seeking methodological knowledge to address biomedical applications, to life science specialists in search of a gentle reference for advanced data analytics. With contributions from internationally renowned experts, the book covers foundational methodologies in a wide spectrum of life science applications including electronic health record processing, diagnostic imaging, text processing, as well as omics-data processing. This survey of consolidated problems is complemented by a selection of advanced applications including cheminformatics and biomedical interaction network analysis. A modern and mindful approach to the use of data-driven methodologies in the life sciences also requires careful consideration of the associated societal, ethical, legal and transparency challenges, covered in the concluding chapters of this book"-- _cPublisher's website.
650			_aMedical informatics. _922457
650			_aArtificial intelligence _xMedical applications. _922458
650			_aBioinformatics. _922459
655			_aElectronic books. _922460
700			_aBacciu, Davide. _922461
700			_aLisboa, P. J. G. _q(Paulo J. G.), _d1958- _922462
700			_aVellido, Alfredo. _922463
856			_uhttps://www.worldscientific.com/worldscibooks/10.1142/q0322#t=toc _zAccess to full text is restricted to subscribers.
942			_cEBK
999			_c13896 _d13896