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Condizione: New.

Condizione: New. In English.

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PAP. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book explores Deep Learning strategies to overcome the challenges of Class Imbalance, Multi-Class Classification, and Multi-Modality Issues in Alzheimer's Disease and Dementia diagnosis. It introduces optimized neural models with better data enhancement techniques to improve the classification accuracy, supporting early and precise detection using MRI, PET, Genetical and Clinical data.This book serves as a detailed guide for researchers, data scientists, and healthcare experts focusing on AI-based Alzheimer's detection. It offers insights into building advanced, efficient, and scalable diagnostic models for neurodegenerative diseases, helping improve accuracy and reliability in early diagnosis.…

PAP. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book presents a comprehensive Artificial Intelligence driven framework for predicting COVID-19 severity in patients with comorbidities, addressing critical challenges in diagnosis, prognosis, and healthcare resource management. It integrates Machine Learning and Deep Learning techniques to analyze large-scale clinical, demographic, and medical imaging data. Imbalanced clinical datasets are handled using advanced preprocessing and resampling strategies, enabling robust prediction of mortality, survival, and disease severity. The book serves as a comprehensive guide for researchers, data scientists, and healthcare professionals interested in AI-based Prediction of COVID-19 Severity in Patients with Comorbidities. It highlights that classical Machine Learning models, including Decision Tree, Random Forest, and Gaussian Naïve Bayes, achieve high precision, while neural network-based models demonstrate strong generalization and robustness.…

Condizione: New. Print on Demand.

Condizione: New. Print on Demand.

Condizione: New. PRINT ON DEMAND.

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Este libro presenta un marco integral impulsado por la Inteligencia Artificial para predecir la gravedad de la COVID-19 en pacientes con comorbilidades, abordando desafíos críticos en el diagnóstico, el pronóstico y la gestión de los recursos sanitarios. Integra técnicas de aprendizaje automático y aprendizaje profundo para analizar datos clínicos, demográficos y de imágenes médicas a gran escala. Los conjuntos de datos clínicos desequilibrados se manejan utilizando estrategias avanzadas de preprocesamiento y remuestreo, lo que permite una predicción robusta de la mortalidad, la supervivencia y la gravedad de la enfermedad.El libro sirve de guía exhaustiva para investigadores, científicos de datos y profesionales sanitarios interesados en la predicción basada en IA de la gravedad de la COVID-19 en pacientes con comorbilidades. Destaca que los modelos clásicos de aprendizaje automático, como el árbol de decisión, el bosque aleatorio y el Bayes Naive gaussiano, logran una gran precisión, mientras que los modelos basados en redes neuronales demuestran una gran generalización y robustez.…