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269179074
Intelligent Systems for Biomedical Signal and Image Processing: Artificial Intelligence in Biomedical Signal and Image Processing: Techniques and
Item #:
269179074
XCD 182
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The introduction of artificial intelligence in healthcare enables accurate, automated, and cost-effective analysis of complicated data.
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Product Details
- The introduction of artificial intelligence in healthcare enables accurate, automated, and cost-effective analysis of complicated data. Biomedical signals, including EEG, ECG, MRI, CT, and X-rays, are needed to diagnose and track medical conditions.AI-driven epilepsy detection technologies use machine learning and deep learning to improve signal quality, extract relevant characteristics, and discover subtle patterns that are hard to detect manually. Biometric medical imaging aids diagnosis and therapy. Biometrics identifies the most relevant and minute features for a rigorous, patient-specific study. It includes data segmentation, extraction, and classification approaches to overcome data dimension complexity. Such an intelligent system holds promise for providing early detection, and real-time monitoring, improving model accuracy and scalability.
| Publisher | LAP LAMBERT Academic Publishing |
| Publication date | April 9, 2025 |
| Language | English |
| Print length | 76 pages |
| ISBN-10 | 6208423708 |
| ISBN-13 | 978-6208423704 |
| Item Weight | 3.99 ounces (113.12 grams) |
| Dimensions | 5.91 x 0.18 x 8.66 inches (15 x 0.5 x 22 cm) |
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Intelligent Systems for Biomedical Signal and Image Processing: Artificial Intelligence in Biomedical Signal and Image Processing: Techniques and Applications
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XCD 182
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Features & Benefits
- AI enhances the analysis of complex biomedical signals for better diagnosis.
- Technologies like machine learning and deep learning improve signal quality in epilepsy detection.
- Biometric imaging facilitates precise diagnosis and therapy for patients.
- Intelligent systems offer early detection and real-time monitoring of medical conditions.
- AI-driven approaches tackle data complexity through effective segmentation, extraction, and classification.
- The system promises improved accuracy and scalability in medical analysis.
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