Biomedical Data Mining for Information Retrieval: Methodologies, Techniques, and

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Condition:
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Hardcover issued without dust-jacket. Bumping to edges of boards. Otherwise, clean and solid.
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Item specifics

Condition
Very Good
A book that has been read but is in excellent condition. No obvious damage to the cover, with the dust jacket included for hard covers. No missing or damaged pages, no creases or tears, and no underlining/highlighting of text or writing in the margins. May be very minimal identifying marks on the inside cover. Very minimal wear and tear. See all condition definitionsopens in a new window or tab
Seller Notes
“Hardcover issued without dust-jacket. Bumping to edges of boards. Otherwise, clean and solid.”
Book Title
Biomedical Data Mining for Information Retrieval: Methodologie
ISBN
9781119711247
Category

About this product

Product Identifiers

Publisher
Wiley & Sons, Incorporated, John
ISBN-10
111971124X
ISBN-13
9781119711247
eBay Product ID (ePID)
13050079165

Product Key Features

Number of Pages
448 Pages
Publication Name
Biomedical Data Mining for Information Retrieval : Methodologies, Techniques, and Applications
Language
English
Publication Year
2021
Subject
General, Databases / Data Mining
Type
Textbook
Author
Subhendu Kumar Pani
Subject Area
Computers, Medical
Series
Artificial Intelligence and Soft Computing for Industrial Transformation Ser.
Format
Hardcover

Dimensions

Item Height
0.4 in
Item Weight
16 Oz
Item Length
0.4 in
Item Width
0.4 in

Additional Product Features

Intended Audience
Scholarly & Professional
Synopsis
BIOMEDICAL DATA MINING FOR INFORMATION RETRIEVAL This book not only emphasizes traditional computational techniques, but discusses data mining, biomedical image processing, information retrieval with broad coverage of basic scientific applications. Biomedical Data Mining for Information Retrieval comprehensively covers the topic of mining biomedical text, images and visual features towards information retrieval. Biomedical and health informatics is an emerging field of research at the intersection of information science, computer science, and healthcare and brings tremendous opportunities and challenges due to easily available and abundant biomedical data for further analysis. The aim of healthcare informatics is to ensure the high-quality, efficient healthcare, better treatment and quality of life by analyzing biomedical and healthcare data including patient's data, electronic health records (EHRs) and lifestyle. Previously, it was a common requirement to have a domain expert to develop a model for biomedical or healthcare; however, recent advancements in representation learning algorithms allows us to automatically to develop the model. Biomedical image mining, a novel research area, due to the vast amount of available biomedical images, increasingly generates and stores digitally. These images are mainly in the form of computed tomography (CT), X-ray, nuclear medicine imaging (PET, SPECT), magnetic resonance imaging (MRI) and ultrasound. Patients' biomedical images can be digitized using data mining techniques and may help in answering several important and critical questions relating to healthcare. Image mining in medicine can help to uncover new relationships between data and reveal new useful information that can be helpful for doctors in treating their patients. Audience Researchers in various fields including computer science, medical informatics, healthcare IOT, artificial intelligence, machine learning, image processing, clinical big data analytics.
LC Classification Number
R859.7.D35

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