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Titlebook: Machine Learning and AI for Healthcare; Big Data for Improve Arjun Panesar Book 2021Latest edition Arjun Panesar 2021 Machine Learing.Artif

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樓主: Addiction
11#
發(fā)表于 2025-3-23 11:14:07 | 只看該作者
Book 2021Latest editionligent systems in healthcare and covers the challenges of managing big data..The book has been updated with the latest research in massive data, machine learning, and AI ethics. It covers new topics in managing the complexities of massive data, and provides examples of complex machine learning model
12#
發(fā)表于 2025-3-23 15:38:44 | 只看該作者
13#
發(fā)表于 2025-3-23 21:32:33 | 只看該作者
Preparing Data,rough feeding models data, thus making the most crucial step in any data or machine learning project cleaning and preparation. It cannot be stressed enough: bad data creates bad results even when fed to the world’s most sophisticated machine learning models.
14#
發(fā)表于 2025-3-23 23:23:08 | 只看該作者
15#
發(fā)表于 2025-3-24 04:53:50 | 只看該作者
https://doi.org/10.1007/978-1-4842-6537-6Machine Learing; Artificial Intelligence; Healthcare; Big Data; Analytics; Real-Time Series; Deep Learning
16#
發(fā)表于 2025-3-24 07:55:22 | 只看該作者
17#
發(fā)表于 2025-3-24 12:16:11 | 只看該作者
18#
發(fā)表于 2025-3-24 17:49:55 | 只看該作者
How to Perform Machine Learning,Machine learning is a rapidly evolving and exciting discipline within computer science, blending a range of skills including exploration and discovery, engineering, and analysis. Machine learning uses large amounts of factual, historical data to help us better understand behaviors.
19#
發(fā)表于 2025-3-24 21:10:47 | 只看該作者
What Is the Future of Healthcare?,New advances in medicine and concepts that were once the futuristic topics of science fiction are gradually becoming a reality. Gene therapies, 3-D printing of human organs, liquid biopsies, robot-assisted surgeries, and voice-enabled personal assistants are now realities that are becoming more sophisticated as time goes on [165–168].
20#
發(fā)表于 2025-3-25 00:00:53 | 只看該作者
Case Studies,AI is improving the healthcare experience, bringing success to those who can leverage and adapt to a new health and care delivery paradigm. This chapter contains real-world case studies where applications of machine learning are being used to solve real-world problems in digital health.
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