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008			211021s2022 nju ob 001 0 eng
015			_aGBC273742 _2bnb
020			_a9781119813040 _q(ebook)
020			_a1119813042
020			_a9781119813026 _q(pdf)
020			_a1119813026
020			_a9781119813033 _q(epub)
020			_a1119813034
020			_z9781119813019 _q(hardback)
035			_a(OCoLC)1284921103 _z(OCoLC)1284918016
037			_a9781119813033 _bWiley
040			_aDLC _beng _erda _cDLC _dOCLCF _dOCLCO _dDG1 _dOCLCO _dUKMGB _dTR-AnTOB
041	0		_aeng
060			_aWG 370
096			_aWG370
245	0	0	_aPredicting heart failure : _binvasive, non-invasive,machine learning and artificial intelligence based methods / _cedited by Kishor Kumar Sadasivuni, Qatar University, Doha, Qatar, [and four others]
264		1	_aHoboken, NJ : _bJohn Wiley & Sons, _c2022
300			_a1 online resource
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
506			_aAvailable to OhioLINK libraries
520			_a"Heart diseases are the deadliest disease in the world. There are many diseases in the heart disease category, the most prominent of them is coronary artery disease (CAD) that causes heart attack. CAD, high blood pressure and many other heart diseases cause HF. HF is a consequence of heart disease and the prediction of HF is related to the prediction of diseases in the category of heart disease. In this chapter, the diagnosis of HF is discussed as invasive / non-invasive and artificial intelligence / machine learning techniques. Invasive and non-invasive techniques make a distinction regarding the way the patient is treated. Invasive methods are usually associated with a physical intervention in the body. This intervention involves operations such as taking blood for blood analysis, not pressing strongly on the abdominal area. Non-invasive methods include methods such as physical therapy, blood pressure and temperature measurement. In today's world where information technologies have evolved in every field, the field of health has also received its share. Computer aided clinical decision support systems provide the strongest support to diagnostic studies today. The most important components of computer-aided diagnosis are artificial intelligence and machine learning. Artificial intelligence and machine learning systems offer a wide range of services from the smart assistant application to the use of imaging techniques. Artificial intelligence and machine learning have a healing role in electrocardiography, echocardiography and similar invasive and non-invasive techniques. In the second part of the chapter, HF will be described and its causes, symptoms and treatment will be revealed. The purpose of the third part is to explain the diagnosis by invasive and non-invasive methods. In the fourth chapter, computer aided diagnosis and decision support systems are briefly mentioned. In the fifth chapter, first what artificial intelligence is, then its fields and examples of artificial intelligence supported studies are presented. In the sixth chapter, what machine learning is, learning types, machine learning algorithms and machine learning based diagnostic studies are explained. Studies are summarized at the end of the chapter and diagnostic studies for HF are commented"-- _cProvided by publisher
650		0	_aHeart failure _0http://id.loc.gov/authorities/subjects/sh85059745 _xRisk factors. _0http://id.loc.gov/authorities/subjects/sh00002541
650		0	_aHeart failure _0http://id.loc.gov/authorities/subjects/sh85059745 _xTreatment. _0http://id.loc.gov/authorities/subjects/sh99005040
650		0	_aHeart _xDiseases _xPatients. _0http://id.loc.gov/authorities/subjects/sh85020188
655		0	_aElectronic books _92032
700	1		_aSadasivuni, Kishor Kumar, _d1986- _0http://id.loc.gov/authorities/names/n2021058632 _eauthor
856	4	0	_3Wiley Online Library _zConnect to resource _uhttps://onlinelibrary.wiley.com/doi/book/10.1002/9781119813040
942			_2NLM _cEBK