AAAI'94 SPRING SYMPOSIUM -- AI IN MEDICINE =========================================== Dear Colleagues: The revised call for papers for the 1994 AI in Medicine symposium is appended below. Two important points in this CFP are: * The clinical data sets are now available via anonymous ftp. The contents of the data sets are described in the CFP. * We set up an experimental 'matchmaker' service to promote collaboration. If you would like to attend the symposium but do not have collaborators with complementary backgrounds, read the section describing this service. Feel free to distribute this CFP to other mailing lists and bulletin boards. Regards, Serdar Uckun / Isaac Kohane, Co-Chairs, AIM-94 --------------------------------------------------------------------------- Call for Papers AAAI 1994 Spring Symposium: Artificial Intelligence in Medicine: Interpreting Clinical Data (March 21-23, 1994, Stanford University, Stanford, CA) The deployment of on-line clinical databases, many supplanting the traditional role of the paper patient chart, has increased rapidly over the past decade. The consequent explosion in the quality and volume of available clinical data, along with an ever more stringent medicolegal obligation to remain aware of all implications of these data, has created a substantial burden for the clinician. The challenge of providing intelligent tools to help clinicians monitor patient clinical courses, forecast likely prognoses, and discover new relational knowledge, is at least as large as that generated by the knowledge explosion which motivated earlier efforts in Artificial Intelligence in Medicine (AIM). Whereas many of the pioneering programs worked on small data sets which were entered interactively by knowledge engineers or clinicians, the current generation of programs have to act on raw data, unfiltered and unmediated by human beings. Interaction with human users typically only occurs on demand or on detection of clinically significant events. The emphasis of this symposium will be on methodologies that provide robust autonomous performance in data-rich clinical environments ranging from busy outpatient practices to operating rooms and intensive care units. Relevant topics include intelligent alarming (including anticipation and prevention of adverse clinical events), data abstraction, sensor validation, preliminary event classification, therapy advice, critiquing, and assistance in the establishment and execution of clinical treatment protocols. Detection of temporal and geographical patterns of disease manifestations and machine learning of clinical patterns are also of interest. Organizing committee Isaac Kohane, Co-chair (Harvard Medical School) Serdar Uckun, Co-chair (Stanford University) Enrico Coiera (Hewlett-Packard Laboratories/Bristol) Ramesh Patil (USC/Information Sciences Institute) Mario Stefanelli (Universita di Pavia) Format Two large data samples are available to serve as training and test sets for various approaches to information management and to provide a common domain of discourse. The samples include: * A dense, high volume data set typical of a critical care environment. This data set consist of hemodynamic measurements, mechanical ventilator settings, laboratory values including arterial blood gas measurements, and treatment information covering a 12-hour period of the ICU treatment of a patient with severe respiratory distress. * A large number of sparse data sets representative of outpatient environments. The data includes blood glucose measurements, treatment, and lifestyle information on 70 patients with diabetes mellitus. Each patient record consists of several weeks' to months' worth of clinical information sampled at irregular intervals. These sets are available immediately to be used as training cases. For interested parties, 10 more case records will be made available two weeks prior to the symposium to be used as an optional testing set for various approaches. The data samples and accompanying clinical information are available via anonymous ftp from HPP.Stanford.EDU (36.44.0.77) in the directory pub/AIM-94. The data will also be made available on diskettes to participants who do not have Internet access. It will be left to the discretion of the participants to use any subset of these samples to help focus their approaches and presentations. The data can also be used as test vehicles for their own research and to create sample programs for demonstration at the symposium. Participants do not have to use the data in order to participate. However, the program committee will favor presentations which exploit the provided data sets in their analyses. AIM-94 Matchmaker Service We realize that an accurate interpretation of clinical data requires a thorough understanding of the physiological principles and clinical issues involved. We also realize that many AIM researchers do not have convenient access to medical expertise, and that a symposium focusing on a clinical theme may catch several parties at a disadvantage. Conversely, some clinical researchers may be interested in participating but may not have collaborators on the computer science end of the field. To offset such disadvantages, we will provide a simple 'Matchmaker' service for AIM-94. The purpose of this service is to establish a medium by which researchers can seek collaborators of complementary background and interests for AIM-94 participation and beyond. If you are interested in participating in this program, send a one-paragraph description of your background, research interests, and the type of collaboration you are pursuing to by September 20th. We will collate these entries and distribute the whole list to all participants of the program. It will be the participants' responsibility to contact others to discuss and establish collaborative efforts; AIM-94 organizers will solely act as mediators. Submission process Potential participants are invited to submit abstracts no longer than 2 pages (< 1200 words) by October 15, 1993. The abstracts should outline methodology and indicate, if applicable, how the provided data may be used as a proof-of-principle for the discussed methodology. Electronic submissions are encouraged. The abstracts may be sent in ASCII, RTF, or PostScript formats to . Authors of accepted abstracts will be asked to submit a working paper by January 31, 1994. They will also be asked to prepare either a poster or an oral presentation. Submissions by mail Use this method ONLY IF you cannot submit an abstract electronically. Fax submissions will not be accepted. Send 6 copies of the abstract to: Serdar Uckun, MD, PhD Co-chair, AIM-94 Knowledge Systems Laboratory, Stanford University 701 Welch Road, Bldg. C Palo Alto, CA 94304, U.S.A. Phone: [+1] (415) 723-1915 Fax: [+1] (415) 725-5850 Calendar Abstracts due: October 15, 1993 Notification of authors by: November 15, 1993 Working papers due: January 31, 1994 Spring Symposium: March 21-23, 1994 Information For further information, please contact the co-chairs at the address above or (preferably) via e-mail at: