Perceptrons: An Introduction to Computational Geometry

By Two Pointerz

Safety pharmacology is the evaluation and study of the pharmacological effects of a potential drug that are unrelated to the desired therapeutic effect. These effects often present a hazard particularly in individuals with compromised or limited organ system functions. Safety Pharmacology in Pharmaceutical Development: Approval and Post Marketing Surveillance, Second Edition covers safety pharmacology from the regulatory requirements down to the studies that must be done to justify them. Using the author s more than 30 years of direct experience, the book incorporates tricks and practical insights for making studies work and understanding why they fail. The second edition includes current regulations, including USFDA and those from Europe and Japan. Presenting a clear description of what is needed and why for supporting drug development, the book focuses on updated test methods, interpretation, and science. It covers the core and supplemental batteries of test procedures and how to do them and provides an overview of available facilities and contract organizations for performing studies.

• Format: Paperback
• Language: English
• ISBN: 0262630222
• ISBN13: 9780262630221
• Release Date: January 1969
• Publisher: MIT Press (MA)
• Length: 268 Pages
• Weight: 0.95 lbs.

Customer Reviews

Deja vu?

In 1958, Cornell psychologist Frank Rosenblatt proposed the 'perceptron', one of the first neural networks to become widely known. A retina sensory layer projected to an association layer made up of threshold logic units which in turn connected to the third layer, the response layer. If two groups of patterns are linearly separable then the perceptron network works well in learning to classify them in separate classes. In...

Seminal AI book

This is a seminal work in the field of Artificial Intelligence. Following an initial period of enthusiasm, the field encountered a period of frustration and disrepute. Minksy and Papert's 1969 book summed up this general feeling of frustration among researchers by demonstrating the representational limitations of Perceptrons (used in neural networks). Their arguments were very influential in the field and accepted by...