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Record Nr. |
UNINA9910734898003321 |
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Autore |
Talukdar Jyotismita |
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Titolo |
Artificial Intelligence in Healthcare Industry / / by Jyotismita Talukdar, Thipendra P. Singh, Basanta Barman |
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Pubbl/distr/stampa |
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Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023 |
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ISBN |
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Edizione |
[1st ed. 2023.] |
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Descrizione fisica |
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1 online resource (208 pages) |
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Collana |
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Advanced Technologies and Societal Change, , 2191-6861 |
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Altri autori (Persone) |
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SinghThipendra P |
BarmanBasanta |
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Disciplina |
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Soggetti |
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Artificial intelligence |
Medical care |
Computational intelligence |
Internet of things |
Database management |
Artificial Intelligence |
Health Care |
Computational Intelligence |
Internet of Things |
Database Management |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Introduction to Human and Artificial Intelligence -- Knowledge Representation and Reasoning -- Methods of Machine Learning -- Supervised learning -- Unsupervised Learning -- Time-series analysis -- Artificial Intelligence in Healthcare -- Rule based expert systems -- Robotic Process Automation: A path to Intelligent Healthcare -- Tools and Technologies for implementing AI approaches in healthcare -- Learning Evaluation for Intelligence -- Ethics of Intelligence. |
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Sommario/riassunto |
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This book presents a systematic evolution of artificial intelligence (AI), its applications, challenges and solutions in the field of healthcare. The book mainly covers the foundations and various methods of learning in artificial intelligence with its application in healthcare industry. This |
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book provides a comprehensive introduction to data analysis using AI as a tool in the generation, normalization and analysis of healthcare data in association with several evaluation techniques and accuracy measurements. The book is divided into three major sections describing the basic foundations of AI and its associated algorithms, history of artificial intelligence in healthcare, recent developments and several modeling techniques for the same. The last section of the book provides insights into several implementations and methods of evaluation and accuracy prediction for healthcare analysis in AI. Extensive use of data for analysis and prediction using several technologies has transformed thelives of normal people indirectly effecting our process to communicate, learn, work and socialize within the society. Thus, the book also provides an insight into the ethics of AI that is very vital in the process of implementation and evaluation of healthcare data. The book provides an organized analysis to a considerable part of data in a digitized society. In view of this, it covers the theory, methodology, perfection and verification of empirical work for health-related data processing. Particular attention is devoted to in-depth experiments and applications. |
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