A novel system for rapidly identifying toxic chemicals.
First-responders have a critical need to rapidly identify toxic chemicals during emergencies. However, current systems such as WISER require a large number of inputs before a chemical can be identified. Here we present a novel system which significantly reduces the number of inputs required to identify a toxic chemical.
Bhavnani
Suresh K
SK
Center for Computational Medicine & Biology, Medical School, Michigan Institute for Clinical & Health Research, Electrical Engineering & Computer Science Department, University of Michigan, Ann Arbor, MI, USA.
Ganesan
Arun
A
Scott
Clayton
C
Weber
Chris
C
Saxman
Paul
P
D004019:Dictionaries, Pharmaceutic as Topic; D004632:Emergency Medical Services / Q000379:methods; D016247:Information Storage and Retrieval / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D011041:Poisoning / Q000145:classification* / Q000517:prevention & control*; D011042:Poisons / Q000145:classification*; D012984:Software; D014481:United States
D011042:Poisons