A CAD system design using iteratively reweighted fuzzy c-means and deep tree training for Alzheimer's disease diagnosis

Sasikala, T.S.

doi:10.1016/j.bspc.2023.105655

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This chapter explores the capability of artificial intelligence (AI) in predicting the development of neurodegenerative sicknesses, in particular focusing on Alzheimer's ailment. The goal is to recognize the cutting-edge nation of AI studies in this area and identify rising superior procedures. Through conducting a complete literature evaluation and reading existing research, the authors spotlight the strengths and barriers of the use of AI for neurodegeneration prediction. Similarly, they discuss the role of huge information, system mastering, and deep mastering strategies in developing accurate and reliable prediction models. These findings endorse that AI has the capacity to seriously enhance early diagnosis and prediction of Alzheimer's disease progression. We conclude with ability future instructions and demanding situations in this unexpectedly increasing studies vicinity

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Intelligent Techniques for Detection and Diagnosis of Neurodegenerative Diseases

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The benefits of AI, such as its ability to analyse vast data sets, identify meaningful patterns, make accurate predictions, and provide reliable recommendations have proven very efficient in early and precise diagnosis of various neurodegenerative diseases. The main aim is to emphasise the potential of machine learning and artificial intelligence to advance neurodegenerative disease evaluation and treatment planning. A brief description of the objectives and the methodologies used for the various intelligent techniques is clearly explained with suitable case studies. The study also demonstrates how AI, machine learning, signal processing, and computer-aided diagnostic technologies have the potential to assist physicians in making better clinical decisions. This proposal outlines a research paper that aims to investigate the different AI and ML techniques and algorithms that are employed in the early diagnosis of three different neurodegenerative diseases namely, Alzheimer's disease (AD), Parkinson's disease (PD), and Amyotrophic lateral sclerosis (ALS).

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A CAD system design using iteratively reweighted fuzzy c-means and deep tree training for Alzheimer's disease diagnosis

Cited by 3 publications

References 32 publications

Multimodal mixing convolutional neural network and transformer for Alzheimer’s disease recognition

Multimodal mixing convolutional neural network and transformer for Alzheimer’s disease recognition

AI in Neurodegeneration Prediction

Intelligent Techniques for Detection and Diagnosis of Neurodegenerative Diseases

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