Advances in Intelligent Disease Diagnosis and Treatment

Research Papers in Honour of Prof. Janusz Kacprzyk for Invaluable Contributions

AvChee-Peng Lim,Ashlesha Vaidya

Häftad, Engelska, 2025

Del i serien Intelligent Systems Reference Library

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Beskrivning

The book delves into innovations in AI and related computing paradigms for disease detection and diagnosis. The collected chapters elucidate the use of a variety of AI and related methodologies to address specific medical challenges. From detecting pancreatic cancer, classifying micro-emboli in stroke diagnosis, to segmenting brain tumours from MRI data, and more, the culmination of these studies underscores the transformative impact AI and digital technologies can have on healthcare, emphasising their potential to enhance medical treatment and improve patient care.

Produktinformation

Utgivningsdatum:2025-09-19
Mått:155 x 235 x 17 mm
Vikt:539 g
Format:Häftad
Språk:Engelska
Serie:Intelligent Systems Reference Library
Antal sidor:304
Förlag:Springer International Publishing AG
ISBN:9783031656422

Utforska kategorier

Biomedicinsk teknik inom Medicin
Tillämpad datateknik inom Data och IT
Artificiell intelligens inom Data och IT

Innehållsförteckning

Recent advances in Artificial Intelligence in Healthcare.- Pancreatic Cancer Classification Using Multimodal Imaging.- Bayesian optimisation active learning semi supervised classification for an automatic microembolus detection system.- Images Processing and Visualization of Brain Tumors.- 3D Lung Tumor Segmentation System using Adaptive Structure Deep Belief Network.- Optimal deep transfer learning models for stenosis detection in X ray angiography images.- Forward Nonlinear Model for Deep Learning of EEG Auditory Attention Detection in Cocktail Party Problem. Computational Intelligence Based Modelling of Polyneuropathy Diagnosis.- Decentralized Diagnostics The Role of Federated Learning in Modern Medical Imaging.- Boundary Detection of Incomplete Shapes in Breast Thermal Images Using Statistical Shape Modeling.- Enhanced Liver Lesion Detection in Multi Phase CT Images using Unsupervised Domain Adaptation and Feature Generalization.- Decision Support System for Skin Lesion Diagnosis using Deep Learning.