TY - GEN
T1 - The "human Cli-Knowme" Project
T2 - 3rd International Workshop on Knowledge Representation for Health Care, KR4HC 2011, Held in Conjunction with the 13th Conference on Artificial Intelligence in Medicine, AIME 2011
AU - Shahar, Yuval
PY - 2012/3/8
Y1 - 2012/3/8
N2 - Currently, most clinical knowledge is in free text and is not easily accessible to clinicians and medical researchers. A major grand challenge for medical informatics is the creation of a distributed, universal, formal, sharable, reusable, and computationally accessible medical knowledge base. The required knowledge consists of both procedural knowledge, such as clinical guidelines, and declarative knowledge, such as context-sensitive interpretations of longitudinal patterns of raw clinical data accumulating from several sources. In this position paper, I first demonstrate the feasibility of such an enterprise, and explain in detail the overall lifecycle of a clinical guideline, by reviewing the main current components and their respective evaluations of one such comprehensive architecture for management of clinical guidelines: The Digital Electronic Guideline Library (DeGeL), a Web-based, modular, distributed architecture that facilitates gradual conversion of clinical guidelines from text to a formal representation in chosen target guideline ontology. The architecture supports guideline classification, semantic markup, context-sensitive search, browsing, run-time application to a specific patient at the point of care, and retrospective quality assessment. The DeGeL architecture operates closely with a declarative-knowledge temporal-abstraction architecture, IDAN. Thus, there is significant evidence that building a distributed, multiple-ontology architecture that caters for the full life cycle of a significant portion of current clinical procedural and declarative knowledge, which I refer to as "the Human Clin-knowme Project," has become a feasible task for a joint, coordinated, international effort involving clinicians and medical informaticians.
AB - Currently, most clinical knowledge is in free text and is not easily accessible to clinicians and medical researchers. A major grand challenge for medical informatics is the creation of a distributed, universal, formal, sharable, reusable, and computationally accessible medical knowledge base. The required knowledge consists of both procedural knowledge, such as clinical guidelines, and declarative knowledge, such as context-sensitive interpretations of longitudinal patterns of raw clinical data accumulating from several sources. In this position paper, I first demonstrate the feasibility of such an enterprise, and explain in detail the overall lifecycle of a clinical guideline, by reviewing the main current components and their respective evaluations of one such comprehensive architecture for management of clinical guidelines: The Digital Electronic Guideline Library (DeGeL), a Web-based, modular, distributed architecture that facilitates gradual conversion of clinical guidelines from text to a formal representation in chosen target guideline ontology. The architecture supports guideline classification, semantic markup, context-sensitive search, browsing, run-time application to a specific patient at the point of care, and retrospective quality assessment. The DeGeL architecture operates closely with a declarative-knowledge temporal-abstraction architecture, IDAN. Thus, there is significant evidence that building a distributed, multiple-ontology architecture that caters for the full life cycle of a significant portion of current clinical procedural and declarative knowledge, which I refer to as "the Human Clin-knowme Project," has become a feasible task for a joint, coordinated, international effort involving clinicians and medical informaticians.
KW - Automatic Application
KW - Clinical Guidelines
KW - Knowledge Acquisition
KW - Medical Decision Support Systems
KW - knowledge Representation
UR - http://www.scopus.com/inward/record.url?scp=84857764261&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-27697-2_1
DO - 10.1007/978-3-642-27697-2_1
M3 - Conference contribution
AN - SCOPUS:84857764261
SN - 9783642276965
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 1
EP - 22
BT - Knowledge Representation for Health-Care - AIME 2011 Workshop KR4HC 2011, Revised Selected Papers
Y2 - 6 July 2011 through 6 July 2011
ER -