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Abstract
In the early 21st century, artificial intelligence began to be used to process medical information. However, before this happened, predictive models used in healthcare could only consider a limited number of variables, and only in properly structured and organised medical data. Today, advanced tools based on machine learning techniques - which, using artificial neural networks, can explore extremely complex relationships - and deep learning technologies effectively support the user in performing parts of healthcare tasks, often resulting in better results that cannot be achieved by humans. AI systems are designed to cope with the complex data generated within modern healthcare. Although deep learning algorithms proved to provide reliable results on variety of data types most common algorithms performs best when applied on images. Therefor in this chapter, the step-by-step process of building the medical application that utilizes the neural network model for image based diagnosis is presented
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- Category:
- Monographic publication
- Type:
- rozdział, artykuł w książce - dziele zbiorowym /podręczniku w języku o zasięgu międzynarodowym
- Language:
- English
- Publication year:
- 2021
- Bibliographic description:
- Kocejko T.: THE ROLE OF INFERENCE IN MOBILE MEDICAL APPLICATION DESIGN// Information technology in biomedical engineering/ : , 2021, s.38-47
- Sources of funding:
-
- Statutory activity/subsidy
- Verified by:
- Gdańsk University of Technology
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