%0 Journal Article %1 arrowsmith.98 %A Smalheiser, Neil R. %A Swanson, Don R. %D 1998 %E (1998), 57 %J Computer Methods Programs in Biomedicine %K CAT CAT-ONLINE-SW CAT-REL-COOR arrowsmith bk-ngx mining text %P 149–153 %T Using ARROWSMITH: a computer-assisted approach to formulating and assessing scientific hypotheses %U http://arrowsmith.psych.uic.edu/arrowsmith_uic/tutorial/swanson_smalheiser_cmpb_1998.pdf %V 57 %X Conventional computer searches of the biomedical literature (e.g. MEDLINE) allow investigators to retrieve much of the information that has already been published on a given topic. However, these searches are of limited utility at the frontier of scientific discovery, when one wishes to identify and assess new, untested scientific hypotheses, or to uncover biologically significant relations between two previously disparate fields of inquiry. We have designed a set of interactive software and database search strategies, collectively called ARROWSMITH, that facilitate the discovery of plausible hypotheses linking findings across specialties (Artif. Intell. 91 (1997) 183–203). In the simplest implementation of ARROWSMITH, the user begins with an experimental finding or hypothesis that two items A and C are related in some way. The titles of papers indexed in MEDLINE which contain the word ‘A’ (or synonyms) are downloaded into a file A, and similarly a file C is created. The software constructs a list of words and phrases B common to files A and C; automatic and manual editing are used to filter out uninteresting B-terms. For each B-term, the software generates an AB file of titles containing both ‘A’ and ‘B’, and a BC file of titles containing both ‘B’ and ‘C’; these titles are juxtaposed to facilitate the user judging whether there is likely to be a biologically significant relation among A, B and C. ARROWSMITH has been employed to analyze research problems relating to oxidative stress, brain damage, Alzheimer’s disease and schizophrenia. Applications of ARROWSMITH include: anticipating adverse drug reactions, identifying mechanisms by which agents modulate cellular or organismal responses, suggesting new therapeutic approaches, identifying possible risk factors for diseases, and identifying potential animal models for human conditions. A simplified experimental version of ARROWSMITH is now freely accessible on the World Wide Web (http://kiwi.uchicago.edu).

@article{arrowsmith.98, abstract = {Conventional computer searches of the biomedical literature (e.g. MEDLINE) allow investigators to retrieve much of the information that has already been published on a given topic. However, these searches are of limited utility at the frontier of scientific discovery, when one wishes to identify and assess new, untested scientific hypotheses, or to uncover biologically significant relations between two previously disparate fields of inquiry. We have designed a set of interactive software and database search strategies, collectively called ARROWSMITH, that facilitate the discovery of plausible hypotheses linking findings across specialties (Artif. Intell. 91 (1997) 183–203). In the simplest implementation of ARROWSMITH, the user begins with an experimental finding or hypothesis that two items A and C are related in some way. The titles of papers indexed in MEDLINE which contain the word ‘A’ (or synonyms) are downloaded into a file A, and similarly a file C is created. The software constructs a list of words and phrases B common to files A and C; automatic and manual editing are used to filter out uninteresting B-terms. For each B-term, the software generates an AB file of titles containing both ‘A’ and ‘B’, and a BC file of titles containing both ‘B’ and ‘C’; these titles are juxtaposed to facilitate the user judging whether there is likely to be a biologically significant relation among A, B and C. ARROWSMITH has been employed to analyze research problems relating to oxidative stress, brain damage, Alzheimer’s disease and schizophrenia. Applications of ARROWSMITH include: anticipating adverse drug reactions, identifying mechanisms by which agents modulate cellular or organismal responses, suggesting new therapeutic approaches, identifying possible risk factors for diseases, and identifying potential animal models for human conditions. A simplified experimental version of ARROWSMITH is now freely accessible on the World Wide Web (http://kiwi.uchicago.edu).}, added-at = {2011-02-17T04:22:56.000+0100}, author = {Smalheiser, Neil R. and Swanson, Don R.}, biburl = {https://www.bibsonomy.org/bibtex/23ec902df89ceb319818f7d93ec9a5c7b/huiyangsfsu}, editor = {(1998), 57}, interhash = {6a9639134d1bf632b0a735999073ceff}, intrahash = {3ec902df89ceb319818f7d93ec9a5c7b}, journal = {Computer Methods Programs in Biomedicine}, keywords = {CAT CAT-ONLINE-SW CAT-REL-COOR arrowsmith bk-ngx mining text}, pages = {149–153}, timestamp = {2011-02-17T04:22:57.000+0100}, title = {Using ARROWSMITH: a computer-assisted approach to formulating and assessing scientific hypotheses}, url = {http://arrowsmith.psych.uic.edu/arrowsmith_uic/tutorial/swanson_smalheiser_cmpb_1998.pdf}, volume = 57, year = 1998 }