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Machine learning for neurodegenerative disorders : advancements and applications
Explores the application of machine learning to the understanding, early diagnosis, and management of neurodegenerative disorders. With a specific focus on its role in ongoing clinical trials, the book covers essential topics such as data collection, pre-processing, feature extraction, model development, and validation techniques. It delves into the applications of neuroimaging techniques like magnetic resonance imaging (MRI), computed tomography (CT), and positron emission tomography (PET) in the diagnosis and understanding of neurodegenerative disorders. Additionally, the book examines various machine-learning algorithms employed for biomarker discovery in neurodegenerative disorders. It highlights the role of neuroinformatics and big data analysis in advancing the understanding and management of neurodegenerative disorders. Furthermore, the book reviews future prospects and presents the ethical considerations and regulatory challenges associated with implementing machine learning approaches in the diagnosis, treatment, and prevention of neurodegenerative disorders.
Clinical metabolomics applications in genetic diseases
Helps readers discover the forefront of personalized medicine on clinical metabolomics and its applications in genetic diseases. This comprehensive guide offers a functional relationship map between cell components and genetic variations in various diseases, providing insights that can be applied to personalized medicine. Covers the latest developments in metabolomics for health, with practical guidance for clinical experts looking to advance their laboratory techniques and career. The metabolomics profile is a powerful tool that has revolutionized our understanding of the relationship between genetics, clinical readouts, and disease outcomes. By integrating metabolomics with genomics and clinical phenotypes, the authors have developed diagnostic and prediction models that have vastly improved patient outcomes and deepened the understanding of disease mechanisms.
