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024 7 _a10.1007/978-981-19-5272-2
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072 7 _aUB
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072 7 _aMED117000
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072 7 _aUXT
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082 0 4 _a610.285
_223
245 1 0 _aArtificial Intelligence in Healthcare
_h[electronic resource] :
_bRecent Applications and Developments /
_cedited by Tianhua Chen, Jenny Carter, Mufti Mahmud, Arjab Singh Khuman.
250 _a1st ed. 2022.
264 1 _aSingapore :
_bSpringer Nature Singapore :
_bImprint: Springer,
_c2022.
300 _aVIII, 227 p. 127 illus., 106 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
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490 1 _aBrain Informatics and Health,
_x2367-1750
505 0 _aChapter 1. Deep fuzzy neural network in dementia -- Chapter 2. Machine learning for COVID detection -- Chapter 3. Machine Learning techniques applied to identify significant gene biomarkers for efficient cancer treatment -- Chapter 4. Group decision making in intelligent medicine -- Chapter 5. Fuzzy logic system for diabetic eye detection -- Chapter 6. Sentiment analysis using deep neural networks -- Chapter 7. The emerging role of AI in dementia research and healthcare -- Chapter 8. Identifying high impact underlying conditions in disease management using AI -- Chapter 9. AI in medicine- case in Asthma diagnosis -- Chapter 10. Sentiment Analysis of Stroke Tweet -- Chapter 11. Artificial intelligence in detecting Alzheimer’s Disease -- Chapter 12. Intelligent systems for IoT based healthcare delivery -- Chapter 13. Machine learning for the detection of Schizophrenia -- Chapter 14. Ictal discharge detection from neuronal signals using machine learning -- Chapter 15. Sentiment analysis for healthcareservice provisioning -- Chapter 16. AI Healthcare: Malignant or Benign -- Chapter 17. Machine learning for dementia diagnosis -- Chapter 18. Using fuzzy systems to calculate blood pressure levels.
520 _aRecent advances in artificial intelligence (AI) and machine learning have witnessed many successes in various disciplines including the healthcare sector. Innovations in intelligent medical systems have revolutionized the way in which healthcare services are provided, ranging from making clinical diagnosis, developing personalized treatment and drugs, assisting patient monitoring, to automating administrative tasks and reducing operational costs. In this book, the authors present key applications in the general area of health care, where AI has made significant successes. From the individual chapters, the readers will be provided with a range of examples to illustrate the wide plethora of application domains utilizing state-of-the-art AI techniques, proving credence to the versatility and effectiveness of an AI approach in health care and medicine. We envisage that this book is ideal for individuals new to the notion of AI in health care, equally, earlycareer academics who wish to further expand on their knowledge in AI in medicine. What will be presented is in no means an exhaustive list of applications, but most definitely a varied one.
650 0 _aMedical informatics.
650 0 _aArtificial intelligence.
650 0 _aArtificial intelligence
_xData processing.
650 1 4 _aHealth Informatics.
650 2 4 _aArtificial Intelligence.
650 2 4 _aData Science.
700 1 _aChen, Tianhua.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aCarter, Jenny.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aMahmud, Mufti.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aKhuman, Arjab Singh.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
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776 0 8 _iPrinted edition:
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776 0 8 _iPrinted edition:
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830 0 _aBrain Informatics and Health,
_x2367-1750
856 4 0 _uhttps://doi.org/10.1007/978-981-19-5272-2
912 _aZDB-2-SCS
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