000			03307nam a2200445 a 4500
001			000q0322
003			WSP
005			20240731095159.0
007			cr |nu|||unuuu
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.)
040			_aWSPC _beng _cWSPC
050		4	_aR858 _b.D43412 2022
072		7	_aCOM _x094000 _2bisacsh
072		7	_aCOM _x016000 _2bisacsh
072		7	_aMED _x009000 _2bisacsh
082	0	4	_a610.285 _223
049			_aMAIN
245	0	0	_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	0		_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.
538			_aMode of access: World Wide Web.
538			_aSystem requirements: Adobe Acrobat Reader.
650		0	_aMedical informatics. _94729
650		0	_aArtificial intelligence _xMedical applications. _94809
650		0	_aBioinformatics. _99561
655		0	_aElectronic books. _93294
700	1		_aBacciu, Davide. _9178279
700	1		_aLisboa, P. J. G. _q(Paulo J. G.), _d1958- _9178280
700	1		_aVellido, Alfredo. _9178281
856	4	0	_uhttps://www.worldscientific.com/worldscibooks/10.1142/q0322#t=toc _zAccess to full text is restricted to subscribers.
942			_cEBK
999			_c97733 _d97733