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

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.