Knowledge-based Expert Systems in Chemistry

Philip Judson

ISBN 10: 1788014715 / ISBN 13: 9781788014717

Published by Royal Society of Chemistry, GB, 2019

About this Item

There have been significant developments in the use of knowledge-based expert systems in chemistry since the first edition of this book was published in 2009. This new edition has been thoroughly revised and updated to reflect the advances.The underlying theme of the book is still the need for computer systems that work with uncertain or qualitative data to support decision-making based on reasoned judgements. With the continuing evolution of regulations for the assessment of chemical hazards, and changes in thinking about how scientific decisions should be made, that need is ever greater. Knowledge-based expert systems are well established in chemistry, especially in relation to toxicology, and they are used routinely to support regulatory submissions. The effectiveness and continued acceptance of computer prediction depends on our ability to assess the trustworthiness of predictions and the validity of the models on which they are based.Written by a pioneer in the field, this book provides an essential reference for anyone interested in the uses of artificial intelligence for decision making in chemistry.

Seller Inventory # LU-9781788014717

Bibliographic Details

• Title: Knowledge-based Expert Systems in Chemistry
• Publisher: Royal Society of Chemistry, GB
• Publication Date: 2019
• Language: English
• ISBN 10: 1788014715
• ISBN 13: 9781788014717
• Binding: Hardback
• Edition: 2nd Edition
• Condition: New
• Weight: 604 grams

About this title

Synopsis

There have been significant developments in the use of knowledge-based expert systems in chemistry since the first edition of this book was published in 2009. This new edition has been thoroughly revised and updated to reflect the advances.

The underlying theme of the book is still the need for computer systems that work with uncertain or qualitative data to support decision-making based on reasoned judgements. With the continuing evolution of regulations for the assessment of chemical hazards, and changes in thinking about how scientific decisions should be made, that need is ever greater. Knowledge-based expert systems are well established in chemistry, especially in relation to toxicology, and they are used routinely to support regulatory submissions. The effectiveness and continued acceptance of computer prediction depends on our ability to assess the trustworthiness of predictions and the validity of the models on which they are based.

Written by a pioneer in the field, this book provides an essential reference for anyone interested in the uses of artificial intelligence for decision making in chemistry.

About the Author

The author studied chemistry at the University of Manchester before working on the synthesis of novel herbicides and fungicides for Fisons Ltd at Chesterford Park Research Station near Saffron Walden. His PhD at the University of Surrey was on chemical synthesis. He took an interest in knowledge-based computer systems and became Head of Chemical Information and Computing for Schering Agrochemicals Ltd. He was one of the founders of Lhasa Limited, a not-for-profit company specialising in knowledge-based expert systems in chemistry including the widely-used Derek, Meteor, and Zeneth systems for predicting chemical toxicity, metabolism, and chemical degradation. Although semi-retired, he continues to contribute to research and development work at Lhasa Limited in his role as Scientific Advisor and is working in a project on synthetic accessibility led by scientists at the US Niational Institutes of Health. He developed and maintains software for chemical hazard classification and chemical safety data sheet management, Harmoneus and Prometheus, which are supplied by Hibiscus plc. He has published over eighty scientfic papers, posters and book chapters. His hobbies include climbing and caving and he has published articles about international caving expeditions that he has taken part in.