Machine Learning for Healthcare

"Machine Learning for Healthcare: Algorithms and Innovations" is a pioneering guide that navigates the intricate fusion of machine learning and healthcare. Focused on demystifying complex algorithms, the book progresses from foundational principles to advanced applications, covering crucial aspects like data preprocessing, model selection, and ethical considerations. Real-world case studies illuminate successful implementations in medical imaging, diagnostics, personalized medicine, and predictive analytics. With an emphasis on collaborative, multidisciplinary approaches, the book underscores the vital partnership between healthcare experts and data scientists. "Machine Learning for Healthcare" serves as an indispensable resource, fostering a deeper understanding of the profound impact of machine learning on the future of healthcare.

Autorentext

Mme Jyoti Kataria est actuellement professeur adjoint à l'École d'ingénierie et de technologie de l'Université K. R. Mangalam. Mme Kataria poursuit actuellement son doctorat dans le domaine de l'informatique et de l'ingénierie. Ses recherches portent sur l'apprentissage automatique, l'apprentissage profond et la vision par ordinateur.

Klappentext

"Machine Learning for Healthcare: Algorithms and Innovations" is a pioneering guide that navigates the intricate fusion of machine learning and healthcare. Focused on demystifying complex algorithms, the book progresses from foundational principles to advanced applications, covering crucial aspects like data preprocessing, model selection, and ethical considerations. Real-world case studies illuminate successful implementations in medical imaging, diagnostics, personalized medicine, and predictive analytics. With an emphasis on collaborative, multidisciplinary approaches, the book underscores the vital partnership between healthcare experts and data scientists. "Machine Learning for Healthcare" serves as an indispensable resource, fostering a deeper understanding of the profound impact of machine learning on the future of healthcare.