Medical Data Processing and Analysis

Wan Azani Mustafa, Hiam Alquran

ISBN 10: 3036580689 / ISBN 13: 9783036580685

Published by Mdpi AG, 2023

About this Item

Seller Inventory # LU-9783036580685

Bibliographic Details

• Title: Medical Data Processing and Analysis
• Publisher: Mdpi AG
• Publication Date: 2023
• Language: English
• ISBN 10: 3036580689
• ISBN 13: 9783036580685
• Binding: Hardback
• Condition: New
• Dimensions: 16.99W x 2.06H x 24.41D centimeters 16.99 centimeters width by 2.06 centimeters height by 24.41 centimeters depth
• Weight: 748 grams

About this title

Synopsis

Medical data can be defined as obtaining information from patients (such as signals, images, sounds, chemical components and their concentration, body temperature, respiratory rate, blood pressure, and different treatment measurements) to quantify the patient's status and disease stage. Computer-aided diagnostic (CAD) systems use classical image processing, computer vision, machine learning, and deep learning methods for image analysis. Using image classification or segmentation algorithms, they find a region of interest (ROI) pointing to a specific location within the given image or an outcome of interest in the form of a label pointing to a diagnosis or prognosis. Computer science, with the evolution of artificial intelligence and machine learning techniques, facilitates the modeling and interpretation of results-from carrying out measurements to experiments and observations. Employing technological tools for collection, processing, and analysis incorporates understanding the patient's status and developing the treatment plan. Achieving highly accurate models requires a huge dataset. This issue can be solved by having enough knowledge around medical data processing and their analysis. This book shows state-of-the-art research in the field of medical data processing and analysis. The medical data are represented in signals, images, raw data, protein sequences, etc. Processing and analysis of any kind can indicate specific issues in the medical sector such as diagnosis, detection, prediction, and segmentation to enhance the visualization of the processed data