Description
Deep Learning in Diabetes Mellitus Detection and Diagnosis presents a thorough examination of how artificial intelligence and deep learning technologies are revolutionizing diabetes detection and diagnosis. Written by experts Jyotismija Chaki and Marcin Wozniak, this 2025 hardcover edition bridges the gap between computer science and healthcare.
The book covers neural network architectures, machine learning algorithms, and their practical applications in identifying diabetes patterns from medical data. It explores how deep learning models can analyze patient information, imaging data, and biomarkers to improve diagnostic accuracy and enable early intervention.
Ideal for researchers, healthcare professionals, and data scientists, this resource provides both theoretical foundations and practical implementations. Readers will gain insights into preprocessing medical data, training robust models, and validating results in clinical settings, making it essential for those advancing AI solutions in endocrinology and preventive medicine.
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