Explainable Artificial Intelligence and Other Soft Computing Techniques: Biomedical and Related Applications

AvNguyen Hoang Phuong,Nguyen Thi Huyen Chau

Inbunden, Engelska, 2026

Del i serien Studies in Systems, Decision and Control

2 600 kr

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Beskrivning

This book shows the state of the art in applications to health and related areas. In the last decades, we all witnessed spectacular successes of AI techniques in many application areas. This book’s chapters show how AI and Computational Intelligence (CI) techniques can help in all aspects of health care: to diagnose diseases, to predict the progress of diseases, and to select appropriate medicine. This book also describes several innovative general AI and CI techniques that can be potentially used both to health problems and to other problems and lists applications of these techniques to areas ranging from engineering to finance and interdisciplinary collaboration.This book can be recommended to practitioners and students interested in learning state-of-the-art AI and CI techniques and their health-related applications, and to researchers interested in improving these techniques.

Produktinformation

Utgivningsdatum:2026-09-06
Mått:155 x 235 x undefined mm
Format:Inbunden
Språk:Engelska
Serie:Studies in Systems, Decision and Control
Förlag:Springer Nature Switzerland AG
ISBN:9783032302113

Utforska kategorier

Biomedicinsk teknik inom Medicin
Artificiell intelligens inom Data och IT

Innehållsförteckning

What If the Resulting Interval Is Too Wide: From a Heuristic Fuzzy-Technique Idea to a Mathematically Justified Approach.- Why Kolmolgorov-Arnold Networks (KAN) Work So Well: A Qualitative Explanation.- A Full Description of All Commutative Associative Polynomial Operations on Probabilities.- To Which Interdisciplinary Research Collaborations Should We Pay More Attention?.- Why Green Wavelength Is Closer to Blue Than to Red and How It Is Related to Computations: Information-Based Explanation.- How to Check Continuity Based on Approximate Measurement Results.- Research on Deep Learning Models for Eye Disease Diagnosis Systems.- Machine Learning for Stroke Analysis and Prediction.- Drug Repositioning by XGBoost for Meta-Paths in Heterogeneous Networks.- Applying A Resampling method for Imbalanced Data in Convolutional Neural Networks Based Classification of Mammograms.- Transfer Learning Method with XAI for Brain Tumor Detection.- Gastrointestinal Disease Diagnosis Using Fused Compressed MobileNetV2 and EfficientNetB0 Models for Endoscopic Image.- Student Emotion Recognition System in the Classroom Using Convolutional Neural Network.- Smote and Random Forest Foresight of Pilot Cognitive Model.- Cervical Spine Fracture Detection on CT Scan Images with Deep Learning and Explainable AI.- Natural Language Processing for Evaluating the Alignment of the Artificial Intelligence and Data Science Curriculum at Thang Long.- Stegano in Images by Huffman Codes and Saliency Map.- Real-time Mixed-Integer Quadratic Programming for Driving Behavior-Inspired Speed Bump Optimal Trajectory Planning.- ERIG: A Framework for Categorizing Skin Conditions utilizing Deep Learning and Integrated Gradients Explanation.- An Efficient Framework for Accurate and Interpretable Fish Disease Classification Using Deep Learning and Integrated Gradients.- Predicting Drug-Disease Associations Using Graph-level Graph Attention Networks and Integrated Similarity Measures.- Relevance Vectors: A Cognitively−Motivated Approach towards Inconsistency in Relevance Assessment.- Student Classification with Preprocessing: A Study on Lightweight Models.- A Method for Handling Imbalanced Data in Predicting TF-Target Gene Interactions Using KNN on Heterogeneous Networks.- Deep-Q learning for physical layer security in IRS-supported UAV communication networks.- Automation of Concrete Compressive Strength Prediction Using H2O AutoML.- Improve the Efficiency of Source Code Plagiarism Detection.- Forex Trading Strategies with Signal Detection Algorithm and Deep Learning.- Addressing Data Imbalance in Job Title Classification Using a Bert Mixture of Experts.- Generating Emotional Classical Piano Music With Conditional Variational Autoencoder.- Tackling New Item Problem Using Weighted ensemble recommendation with Image-based filtering.- Deep learning approaches for segmentation, detection, and classification of lung diseases in X-ray imaging.