000			04159nam a22005895i 4500
999			_c200458362 _d76574
003			TR-AnTOB
005			20231120114942.0
007			cr nn 008mamaa
008			220210s2022 sz | s |||| 0|eng d
020			_a9783030911812
024	7		_a10.1007/978-3-030-91181-2 _2doi
040			_aTR-AnTOB _beng _erda _cTR-AnTOB
041			_aeng
060			_aW 26.55.A7
072		7	_aTJK _2bicssc
072		7	_aTEC041000 _2bisacsh
072		7	_aTJK _2thema
096			_aW26.55.A7EBK
245	1	0	_aIntegrating Artificial Intelligence and IoT for Advanced Health Informatics _h[electronic resource] : _bAI in the Healthcare Sector / _cedited by Carmela Comito, Agostino Forestiero, Ester Zumpano.
250			_a1st ed. 2022.
264		1	_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2022.
300			_a1 online resource
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aInternet of Things, Technology, Communications and Computing, _x2199-1081
505	0		_a1. Lower-Gait Tracking Application Using Smartphones and Tablets -- 2. One-class classification approach in accelerometer based remote monitoring of physical activities for healthcare applications -- 3. Detecting and monitoring behavioural patterns in individuals with cognitive disorders in the home environment with partial annotations -- 4. Towards On-device Weight Monitoring from Selfie Face Images Using Smartphones -- 5. Convergence between IoT and AI for Smart Health and Predictive Medicine -- 6. An Artificial Intelligence and Internet of Things Platform for Healthcare and Industrial Applications -- 7. Methods in Digital Mental Health: Smartphone-based Assessment and Intervention for Stress, Anxiety and Depression -- 8. AI for the detection of the Diabetic Retinopathy -- 9. Enhancing EEG-based Emotion Recognition with Fast Online Instance Transfer -- 10. Using Association Rules to mine Actionable Knowledge from Internet of Medical Thinks data.
520			_aThe book covers the integration of Internet of Things (IoT) and Artificial Intelligence (AI) to tackle applications in smart healthcare. The authors discuss efficient means to collect, monitor, control, optimize, model, and predict healthcare data using AI and IoT. The book presents the many advantages and improvements in the smart healthcare field, in which ubiquitous computing and traditional computational methods alone are often inadequate. AI techniques are presented that play a crucial role in dealing with large amounts of heterogeneous, multi-scale and multi-modal data coming from IoT infrastructures. The book is intended to cover how the fusion of IoT and AI allows the design of models, methodologies, algorithms, evaluation benchmarks, and tools can address challenging problems related to health informatics, healthcare, and wellbeing.
650		0	_aTelecommunication.
650		0	_aCooperating objects (Computer systems).
650		0	_aMedical informatics.
650		0	_aBiomedical engineering.
650	1	4	_aCommunications Engineering, Networks.
650	2	4	_aCyber-Physical Systems.
650	2	4	_aHealth Informatics.
650	2	4	_aBiomedical Engineering and Bioengineering.
653		0	_aArtificial Intelligence
653		0	_aMedical Informatics
653		0	_aInternet of Things
700	1		_aComito, Carmela. _eeditor. _0(orcid)0000-0001-9116-4323 _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aForestiero, Agostino. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aZumpano, Ester. _eeditor. _0(orcid)0000-0003-1129-3737 _4edt _4http://id.loc.gov/vocabulary/relators/edt
710	2		_aSpringerLink (Online service)
830		0	_aInternet of Things, Technology, Communications and Computing, _x2199-1081
856	4	0	_uhttps://doi.org/10.1007/978-3-030-91181-2 _3Springer eBooks _zOnline access link to the resource
942			_2NLM _cEBK