MedRACER'18: Reasoning with Ambiguous and Conflicting Evidence and Recommendations in Medicine

MedRACER will be hosted as a KR 2018 workshop, and will take place in Tempe, Arizona, USA on the 29th of October 2018.

Health care is a sensitive area due to the sheer amount and nature of the information used to manage patients. Medical reasoning is complex and involves multiple interactions among health conditions, treatments, and expectations from both health professionals and patients. Incomplete and contradictory information is ever present and decisions have to be made relying on it. As such, in order to support these professionals in their activities, it is necessary to accurately capture the constraints of medical reasoning in representations than can be used for supporting decisions, synthesizing medical evidence, discovering conflicts and inconsistencies, and so forth. Computational methods provide ways to analyse the available information and apply medical knowledge to it in order to evaluate the possible conclusions/claims, by considering reasons for and against them. They also allow to center the decisions on patients and their needs, as well as to take into account the preferences of various parties (patient, clinician, health center etc.). We aim to explore computational methods – including defeasible reasoning, computational argumentation, (various forms of) logic programming, ontological inference, machine-interpretable clinical pathways, decision support and recommendation systems, preference-based reasoning – for representation of, reasoning with, and resolving conflicts within, medical knowledge.

The aim of this workshop is to bring together researchers from the fields of (various) computational logics, argumentation, defeasible reasoning and reasoning within KR at large, who are interested in health care and would like to share their perspectives on applications of their research to the medical domain. This workshop is a venue for those researchers to share ways their theories and techniques can be used to support reasoning with medical knowledge, focusing especially on the resolution of conflicts in the context of incomplete information. Furthermore, the workshop intends to establish new collaborations to advance the latest computational models for supporting decision-making in health care.

The workshop will feature original contributions in the form of mature papers or work in progress.

Topics​ of Interest ​

We specifically seek works on computational methods for health care, and welcome submissions on health care-related:

Argumentation
Automated reasoning
Case-based reasoning
Defeasible (common-sense, non-monotonic, default) reasoning
Inconsistency handling and conflict resolution
(Answer set, Inductive, Constraint) Logic programming
Ontology-based inference
Probabilistic inference
Information mining from clinical data and documents
Persuasion systems
Expert systems for health care

We solicit works on clinical decision support and particularly invite to submit papers on reasoning with clinical data, including:

Computer-Interpretable guidelines and pathways
Health technology assessments
Clinical trials, cohort, retrospective and network studies, as well as other raw data
Electronic health records
​
Submission Guidelines

Paper submission deadline: 21 July 2018 ​
Submissions should be up to 9 pages in PDF format, including abstract, figures, and references and according to the AAAI style. The reviewing will be single-blind.

All submissions will be made electronically, through the EasyChair conference system:
https://easychair.org/conferences/?conf=medracer18

To download the AAAI author kit:
http://www.aaai.org/Publications/Templates/AuthorKit18.zip

Accepted papers will be included in non-archival workshop proceedings after a careful review process. At least one of the authors will be required to register and attend the KR conference to present the paper in order to include the paper in the workshop proceedings.

Organisers

​Contact email: medracer18@easychair.org​

Kristijonas Čyras (Imperial College London)
Tiago Oliveira (National Institute of Informatics)
Matthew Williams (Imperial College London)