Predictive Modeling in Biomedical Data Mining and Analysis
- Publisher's listprice EUR 160.00
-
67 872 Ft (64 640 Ft + 5% VAT)
The price is estimated because at the time of ordering we do not know what conversion rates will apply to HUF / product currency when the book arrives. In case HUF is weaker, the price increases slightly, in case HUF is stronger, the price goes lower slightly.
- Discount 10% (cc. 6 787 Ft off)
- Discounted price 61 085 Ft (58 176 Ft + 5% VAT)
67 872 Ft
Availability
printed on demand
Why don't you give exact delivery time?
Delivery time is estimated on our previous experiences. We give estimations only, because we order from outside Hungary, and the delivery time mainly depends on how quickly the publisher supplies the book. Faster or slower deliveries both happen, but we do our best to supply as quickly as possible.
Product details:
- Publisher Academic Press
- Date of Publication 26 August 2022
- ISBN 9780323998642
- Binding Paperback
- No. of pages344 pages
- Size 234x190 mm
- Weight 700 g
- Language English
- Illustrations 80 illustrations (30 in full color) 449
Categories
Long description:
Predictive Modeling in Biomedical Data Mining and Analysis presents major technical advancements and research findings in the field of machine learning in biomedical image and data analysis. The book examines recent technologies and studies in preclinical and clinical practice in computational intelligence. The authors present leading-edge research in the science of processing, analyzing and utilizing all aspects of advanced computational machine learning in biomedical image and data analysis. As the application of machine learning is spreading to a variety of biomedical problems, including automatic image segmentation, image classification, disease classification, fundamental biological processes, and treatments, this is an ideal reference.
Machine Learning techniques are used as predictive models for many types of applications, including biomedical applications. These techniques have shown impressive results across a variety of domains in biomedical engineering research. Biology and medicine are data-rich disciplines, but the data are complex and often ill-understood, hence the need for new resources and information.
MoreTable of Contents:
1. Data mining with deep learning in biomedical data
2. Applications of supervised machine learning techniques with the goal of medical analysis and prediction: a case study of breast cancer
3. Medical decision support system using data mining
4. Role of AI techniques in enhancing multi-modality medical image fusion results
5. A comparative performance analysis of backpropagation training optimizers to estimate clinical gait mechanics
6. High-performance medicine in cognitive impairment: Brain-computer interfacing for prodromal Alzheimer's disease
7. Machine learning in healthcare: Brain tumor classifications by gradient and XG boosting models
8. Biofeedback method for human-computer interaction to improve elder caring: Eye gaze tracking
9. Blood screening parameters prediction for preliminary analysis using neural networks
10. Classification of hypertension using the improved unsupervised learning technique and image processing
11. Biomedical data visualization and clinical decision-making in rodents using a multi-usage wireless brain stimulator using novel embedded design
12. LSTM neural network-based classification of sensory signals for healthy and unhealthy gait assessment
13. Addressing challenges and roadblocks in iomedical data using data-driven machine learning
14. Multibjective evolutionary algorithm based on decomposition for feature selection in medical diagnosis
15. Machine learning techniques in healthcare informatics: Showcasing prediction of type 2 diabetes mellitus disease using lifestyle data
