Smart Induction System Based on Intelligent Agent
Case Study: Predicting Diabetic Early Re-admission
(Sprache: Englisch)
Now days, new methodology that deals with induction system including intelligent agents with different types of machine learning techniques based on rules can be suggested. Diagnosis domain is the most appropriate topic for this methodology, especially,...
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Now days, new methodology that deals with induction system including intelligent agents with different types of machine learning techniques based on rules can be suggested. Diagnosis domain is the most appropriate topic for this methodology, especially, diagnosis in health care system.Diabetes is among the commonly known autoimmune diseases, diabetes also predisposes the sufferers to high chances of bacterial and viral infections due to the weakness of the immune system. Diabetic patients are normally more prone to infections and once infected, usually takes time to heal. Hence, more attention is given to wellness as a preventative approach in healthcare. Meanwhile, the development of a diabetes prediction model is an extraordinary change to healthcare approach on the perspective of data-analysis & decision-making level. In this book, prediction of diabetic early readmission using different inductive learning algorithms and intelligent agents has been proposed depending on the pre-diagnosis of the patient.
Autoren-Porträt von Zainab Talib Al-Ars, Abbas Mohsin AL-Bakry
Al-Ars, Zainab TalibZainab Talib Al-Ars: Born in 1984, hold B.Sc.(2006) and M.Sc.(2014) degree in computer science from Baghdad University and a PhD in Artificial Intelligence from the Iraqi Commission for Computers and Informatics since 2020, she has worked as a lecturer at Baghdad University / College of Science, a leading publisher in Computer and Applied Sciences.
Bibliographische Angaben
- Autoren: Zainab Talib Al-Ars , Abbas Mohsin AL-Bakry
- 2021, 284 Seiten, Maße: 22 cm, Kartoniert (TB), Englisch
- Verlag: LAP Lambert Academic Publishing
- ISBN-10: 6203195367
- ISBN-13: 9786203195361
Sprache:
Englisch
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