Titlebook: Advances in Intelligent Disease Diagnosis and Treatment; Research Papers in H Chee-Peng Lim,Ashlesha Vaidya,Lakhmi C. Jain Book 2024 The Ed

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Images Processing and Visualization of Brain Tumors,main requests of medical specialists are taken into account. The work shows that based on the developed methodology 3D modeling of brain tumor MRI data from a set of 2D images (DICOM) provide realistic visualization.

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3D Lung Tumor Segmentation System Using Adaptive Structural Deep Belief Network,ion, a framework which realizes a series of medical imaging analysis for medical professionals in clinics is proposed as the utilization of our Adaptive DBN model, from collecting data to model training, inference, and re-training for new data.

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Forward Nonlinear Model for Deep Learning of EEG Auditory Attention Detection in Cocktail Party Problem, they have some inherent limitations. The main objective of this contribution is to show that nonlinear modeling of speech-electroencephalography system ensures the best performance in terms of higher correlation between stimulus and neural response, thus proving the limitations of linear appro

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Computational Intelligence Based Modelling of Polyneuropathy Diagnosis,o Intensity in diagnosing specific PNP types. The work contributes to data analysis and medical knowledge, providing valuable insights for informed decision-making in the polyneuropathy diagnostic process. Future research avenues include refining data preprocessing and exploring the cost implication

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Decision Support System for Skin Lesion Diagnosis Using Deep Learning, full-supervised deep learning procedure with small scale of labeled training samples. Benefitting from the maintained knowledge in the pretrained network, the finally constructed model even with a limited number of annotated samples, can be expected to produce promising classification performance.

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