Clinical Herbal Prescriptions Principles And Practices Of Herbal Formulations From Deep Learning Health Insurance Herbal Prescription Big Data

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Clinical Herbal Prescriptions: Principles And Practices Of Herbal Formulations From Deep Learning Health Insurance Herbal Prescription Big Data

Clinical Herbal Prescriptions: Principles And Practices Of Herbal Formulations From Deep Learning Health Insurance Herbal Prescription Big Data
Author :
Publisher : World Scientific
Total Pages : 519
Release :
ISBN-10 : 9789813278264
ISBN-13 : 9813278269
Rating : 4/5 (269 Downloads)

Book Synopsis Clinical Herbal Prescriptions: Principles And Practices Of Herbal Formulations From Deep Learning Health Insurance Herbal Prescription Big Data by : Sun-chong Wang

Download or read book Clinical Herbal Prescriptions: Principles And Practices Of Herbal Formulations From Deep Learning Health Insurance Herbal Prescription Big Data written by Sun-chong Wang and published by World Scientific. This book was released on 2019-01-22 with total page 519 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since AlphaGo defeated Ke Jie (who was then ranked 1st among all human players worldwide) May 2017, the art of Go (otherwise known as Weiqi) has entered a new era. Similarly, if we apply artificial intelligence (AI) to herbal medicine, the art of herbal prescription can experience a game change too. The author of this book has done exactly that, and via reverse engineering of the trained AI, the book details how one can compose herbal prescriptions from scratch.As artificial intelligence (AI) technologies outperform humans in such tasks as image/voice recognition and language translation, mastering of concentrated herbal extract granules (CHEG) prescription composition by AI is not a fiction, provided large quantities of high-quality CHEG prescription data are available. Thanks to the 340 million records of modern Western medicine diagnoses and corresponding CHEG prescriptions in the National Health Insurance Reimbursement Database (Taiwan) recorded in the decade between 2004 and 2013, the book is based on the results of applying state-of-the-art deep learning technologies to the CHEG prescription big data.


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