| 期刊全稱(chēng) | AI for Healthcare with Keras and Tensorflow 2.0 | | 期刊簡(jiǎn)稱(chēng) | Design, Develop, and | | 影響因子2023 | Anshik | | 視頻video | http://file.papertrans.cn/143/142818/142818.mp4 | | 發(fā)行地址 | Provides comprehensive and clear coverage of algorithms and techniques.Teaches you different problem areas within the healthcare industry and solves them in a code-first approach.Presents advanced top | | 圖書(shū)封面 |  | | 影響因子 | Learn how AI impacts the healthcare ecosystem through real-life case studies with TensorFlow 2.0 and other machine learning (ML) libraries..This book begins by explaining the dynamics of the healthcare market, including the role of stakeholders such as healthcare professionals, patients, and payers. Then it moves into the case studies. The case studies start with EHR data and how you can account for sub-populations using a multi-task setup when you are working on any downstream task. You also will try to predict ICD-9 codes using the same data. You will study transformer models. And you will be exposed to the challenges of applying modern ML techniques to highly sensitive data in healthcare using federated learning. You will look at semi-supervised approaches that are used in a low training data setting, a case very often observed in specialized domains such as healthcare. You will be introduced to applications of advanced topics such as the graph convolutional network and how you can develop and optimize image analysis pipelines when using 2D and 3D medical images. The concluding section shows you how to build and design a closed-domain Q&A system with paraphrasing, re-ranking, an | | Pindex | Book 2021 |
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