title: A novel system for rapidly identifying toxic chemicals.
abstract: 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.
authors.affiliation: 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.
authors.forename: Suresh K
authors.initials: SK
authors.lastname: Bhavnani
authors.forename: Arun
authors.initials: A
authors.lastname: Ganesan
authors.forename: Clayton
authors.initials: C
authors.lastname: Scott
authors.forename: Chris
authors.initials: C
authors.lastname: Weber
authors.forename: Paul
authors.initials: P
authors.lastname: Saxman
mesh_terms: 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
chemical_list: D011042:Poisons