TY - JOUR
T1 - The coming of age of artificial intelligence in medicine
AU - Patel, Vimla
AU - Shortliffe, Edward H.
AU - Stefanelli, Mario
AU - Szolovits, Peter
AU - Berthold, Michael R.
AU - Bellazzi, Riccardo
AU - Abu-Hanna, Ameen
N1 - Funding Information:
This paper was prepared with partial support from the National Library of Medicine under grant R01 LM07894.
PY - 2009/5
Y1 - 2009/5
N2 - This paper is based on a panel discussion held at the Artificial Intelligence in Medicine Europe (AIME) conference in Amsterdam, The Netherlands, in July 2007. It had been more than 15 years since Edward Shortliffe gave a talk at AIME in which he characterized artificial intelligence (AI) in medicine as being in its "adolescence" (Shortliffe EH. The adolescence of AI in medicine: will the field come of age in the '90s? Artificial Intelligence in Medicine 1993;5:93-106). In this article, the discussants reflect on medical AI research during the subsequent years and characterize the maturity and influence that has been achieved to date. Participants focus on their personal areas of expertise, ranging from clinical decision-making, reasoning under uncertainty, and knowledge representation to systems integration, translational bioinformatics, and cognitive issues in both the modeling of expertise and the creation of acceptable systems.
AB - This paper is based on a panel discussion held at the Artificial Intelligence in Medicine Europe (AIME) conference in Amsterdam, The Netherlands, in July 2007. It had been more than 15 years since Edward Shortliffe gave a talk at AIME in which he characterized artificial intelligence (AI) in medicine as being in its "adolescence" (Shortliffe EH. The adolescence of AI in medicine: will the field come of age in the '90s? Artificial Intelligence in Medicine 1993;5:93-106). In this article, the discussants reflect on medical AI research during the subsequent years and characterize the maturity and influence that has been achieved to date. Participants focus on their personal areas of expertise, ranging from clinical decision-making, reasoning under uncertainty, and knowledge representation to systems integration, translational bioinformatics, and cognitive issues in both the modeling of expertise and the creation of acceptable systems.
KW - Artificial intelligence in medicine, history
KW - Barriers to success
KW - Research challenges
KW - Sociocultural and cognitive factors
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U2 - 10.1016/j.artmed.2008.07.017
DO - 10.1016/j.artmed.2008.07.017
M3 - Article
C2 - 18790621
AN - SCOPUS:64549138950
SN - 0933-3657
VL - 46
SP - 5
EP - 17
JO - Artificial intelligence in medicine
JF - Artificial intelligence in medicine
IS - 1
ER -