Название: Optimized Predictive Models in Health Care Using Machine Learning
Автор: Sandeep Kumar, Anuj Sharma, Navneet Kaur, Lokesh Pawar
Издательство: Wiley-Scrivener
Год: 2024
Страниц: 385
Язык: английский
Формат: pdf (true)
Размер: 34.4 MB
This book is a comprehensive guide to developing and implementing optimized predictive models in healthcare using Machine Learning and is a required resource for researchers, healthcare professionals, and students who wish to know more about real-time applications. The book focuses on how humans and computers interact to ever-increasing levels of complexity and simplicity and provides content on the theory of optimized predictive model design, evaluation, and user diversity. Predictive modeling, a field of Machine Learning, has emerged as a powerful tool in healthcare for identifying high-risk patients, predicting disease progression, and optimizing treatment plans. By leveraging data from various sources, predictive models can help healthcare providers make informed decisions, resulting in better patient outcomes and reduced costs. Deep Learning (DL) algorithms are crucial for enterprises to make business choices based on predictions. DL performs automatic data-oriented feature extraction and learns representations from raw data, unlike conventional ML algorithms. DL models use several neural network-based processing layers to understand illustrations of data with different levels of abstraction.
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