logo

EbookBell.com

Most ebook files are in PDF format, so you can easily read them using various software such as Foxit Reader or directly on the Google Chrome browser.
Some ebook files are released by publishers in other formats such as .awz, .mobi, .epub, .fb2, etc. You may need to install specific software to read these formats on mobile/PC, such as Calibre.

Please read the tutorial at this link:  https://ebookbell.com/faq 


We offer FREE conversion to the popular formats you request; however, this may take some time. Therefore, right after payment, please email us, and we will try to provide the service as quickly as possible.


For some exceptional file formats or broken links (if any), please refrain from opening any disputes. Instead, email us first, and we will try to assist within a maximum of 6 hours.

EbookBell Team

Deep Learning Techniques For Biomedical And Health Informatics 1st Ed 2020 Sujata Dash

  • SKU: BELL-10801326
Deep Learning Techniques For Biomedical And Health Informatics 1st Ed 2020 Sujata Dash
$ 31.00 $ 45.00 (-31%)

4.3

68 reviews

Deep Learning Techniques For Biomedical And Health Informatics 1st Ed 2020 Sujata Dash instant download after payment.

Publisher: Springer International Publishing
File Extension: PDF
File size: 11.23 MB
Author: Sujata Dash, Biswa Ranjan Acharya, Mamta Mittal, Ajith Abraham, Arpad Kelemen
ISBN: 9783030339654, 9783030339661, 3030339653, 3030339661
Language: English
Year: 2020
Edition: 1st ed. 2020

Product desciption

Deep Learning Techniques For Biomedical And Health Informatics 1st Ed 2020 Sujata Dash by Sujata Dash, Biswa Ranjan Acharya, Mamta Mittal, Ajith Abraham, Arpad Kelemen 9783030339654, 9783030339661, 3030339653, 3030339661 instant download after payment.

This book presents a collection of state-of-the-art approaches for deep-learning-based biomedical and health-related applications. The aim of healthcare informatics is to ensure high-quality, efficient health care, and better treatment and quality of life by efficiently analyzing abundant biomedical and healthcare data, including patient data and electronic health records (EHRs), as well as lifestyle problems. In the past, it was common to have a domain expert to develop a model for biomedical or health care applications; however, recent advances in the representation of learning algorithms (deep learning techniques) make it possible to automatically recognize the patterns and represent the given data for the development of such model.

This book allows new researchers and practitioners working in the field to quickly understand the best-performing methods. It also enables them to compare different approaches and carry forward their research in an important area that has a direct impact on improving the human life and health.

It is intended for researchers, academics, industry professionals, and those at technical institutes and R&D organizations, as well as students working in the fields of machine learning, deep learning, biomedical engineering, health informatics, and related fields.

Related Products