Artificial Intelligence for Drug Development, Precision Medicine, and Healthcare

Rezensionen / Stimmen

'this book offers a comprehensive review of AI, deep learning, and machine learning applications in medical sciences. This book (particularly Chapter 5 and onwards) will be useful for both masters and undergraduate students in biostatistics, who are planning to pursue research in AI towards biomedical applications.'

- Chitaranjan Mahapatra, International Society for Clinical Biostatistics, 71, 2021 "This is an interesting and informative book...The book contains R code for many applications so the reader can immediately put many of the ideas into practice by adapting the R code."
- Peter Wludyka, in Technometrics, October 2020

"This book would be a neat addition to the practitioner's reference library of statistical methodologies for healthcare data analysis based on artificial intelligence (AI) and machine learning. The technical narrative is written in recipes; these are sandwiched between a high-level introduction (comprising modern AI and machine learning, classical statistics, and the similarity principle) and an epilogue espousing the author's perspectives about future progress in modern AI. The statistical recipes include example R programming code for the following methodologies (...). It is a compactly written book that could serve as a handy reference guide (i.e., cookbook) for the practitioner who would need to quickly review a new methodology and understand the bigger picture as it would relate to applications in healthcare."
- Frank Yoon in International Statistics Review, March 2021