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Beschreibung
Artificial intelligence (AI) is a branch of computer science that deals with the problem-solving by the aid of symbolic programming. It has greatly evolved into a science of problem-solving with huge applications in business, health care, and engineering. One of the pivotal applications of AI is the development of the expert system. With the advent of big data and AI, robots are now becoming more trustworthy for doctors, and a large number of institutions are now employing robots along with human supervision to carry out activities that were previously done by humans. The major advantage of AI is that it reduces the time that is needed for drug development and, in turn, it reduces the costs that are associated with drug development, enhances the returns on investment and may even cause a decrease in cost for the end user. Future toxicity and safety challenges, including increased polypharmacy and patient diversity, stress the limits of these traditional tools. Massive amounts of newly available data present an opportunity for using artificial intelligence (AI) and machine learning to improve drug safety science.
Artificial intelligence (AI) is a branch of computer science that deals with the problem-solving by the aid of symbolic programming. It has greatly evolved into a science of problem-solving with huge applications in business, health care, and engineering. One of the pivotal applications of AI is the development of the expert system. With the advent of big data and AI, robots are now becoming more trustworthy for doctors, and a large number of institutions are now employing robots along with human supervision to carry out activities that were previously done by humans. The major advantage of AI is that it reduces the time that is needed for drug development and, in turn, it reduces the costs that are associated with drug development, enhances the returns on investment and may even cause a decrease in cost for the end user. Future toxicity and safety challenges, including increased polypharmacy and patient diversity, stress the limits of these traditional tools. Massive amounts of newly available data present an opportunity for using artificial intelligence (AI) and machine learning to improve drug safety science.
Über den Autor
Nagaraju Bandaru. Completed his M.Pharm; Ph.D in department of Pharmacology. His Ph.D area is neuropharmacology. Presently, is working as Assistant Professor in College of Pharmacy, K L University, Vaddeswaram, Guntur, AP, and India. Has qualified with 91.8 percentile in GPAT and also NIPER. Published 40 research articles.
Details
Erscheinungsjahr: | 2021 |
---|---|
Fachbereich: | Toxikologie |
Genre: | Medizin |
Rubrik: | Wissenschaften |
Medium: | Taschenbuch |
ISBN-13: | 9786203471694 |
ISBN-10: | 6203471690 |
Sprache: | Englisch |
Ausstattung / Beilage: | Paperback |
Einband: | Kartoniert / Broschiert |
Autor: | Bandaru, Nagaraju |
Hersteller: | LAP LAMBERT Academic Publishing |
Maße: | 220 x 150 x 4 mm |
Von/Mit: | Nagaraju Bandaru |
Erscheinungsdatum: | 12.03.2021 |
Gewicht: | 0,096 kg |
Über den Autor
Nagaraju Bandaru. Completed his M.Pharm; Ph.D in department of Pharmacology. His Ph.D area is neuropharmacology. Presently, is working as Assistant Professor in College of Pharmacy, K L University, Vaddeswaram, Guntur, AP, and India. Has qualified with 91.8 percentile in GPAT and also NIPER. Published 40 research articles.
Details
Erscheinungsjahr: | 2021 |
---|---|
Fachbereich: | Toxikologie |
Genre: | Medizin |
Rubrik: | Wissenschaften |
Medium: | Taschenbuch |
ISBN-13: | 9786203471694 |
ISBN-10: | 6203471690 |
Sprache: | Englisch |
Ausstattung / Beilage: | Paperback |
Einband: | Kartoniert / Broschiert |
Autor: | Bandaru, Nagaraju |
Hersteller: | LAP LAMBERT Academic Publishing |
Maße: | 220 x 150 x 4 mm |
Von/Mit: | Nagaraju Bandaru |
Erscheinungsdatum: | 12.03.2021 |
Gewicht: | 0,096 kg |
Warnhinweis