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Technologies of Time |

Dimension of Time in Illness: An Objective View

Yuval Shahar, MD, PhD
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From Stanford University, Stanford, California.

Acknowledgments: The author thanks Ms. Kathleen Jones and Ms. Barbara Morgan for assisting in the editing of the paper.

Grant Support: By the National Library of Medicine (LM06245) and the National Science Foundation (IRI-9528444).

Requests for Reprints: Yuval Shahar, MD, PhD, Stanford Medical Informatics, Medical School Office Building x215, 251 Campus Drive, Stanford University, Stanford, CA 94305-5479; e-mail, shahar@smi.stanford.edu. For reprint orders in quantities exceeding 100, please contact the Reprints Coordinator; phone, 215-351-2657; e-mail, reprints@mail.acponline.org.

Ann Intern Med. 2000;132(1):45-53. doi:10.7326/0003-4819-132-1-200001040-00008
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As a professional medical informatician whose main interest is harnessing artificial intelligence and other techniques of information sciences to help both health care providers and patients, I am repeatedly impressed by the tasks that clinicians achieve on a daily basis. Although these tasks require extensive knowledge about both medicine and the world at large, clinicians rarely express any sense of wonder at their accomplishments and usually take them in stride. I can only hope that my computer programs will some day be able to carry out a small fraction of these tasks.

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Figure 2.
Monitoring a patient with type 1 diabetes mellitus (DM).

Arrows represent open context intervals; solid lines represent abstraction intervals; circles represent prelunch glucose level. GLS_DM_PS = glucose-state abstraction in the DM and presupper (composite) context; GLS_DM_Preprandial = glucose-state abstraction in the DM and preprandial (composite) context; H = high; L = low; N = normal. + = prebreakfast glucose level; = presupper glucose level. To convert mg/dL to mmol/L, multiply by 0.5551.

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Figure 1.
Temporal abstraction of platelet and granulocyte values during administration of a prednisone-azathioprine (PAZ) clinical protocol in patients with chronic graft-versus-host disease (CGVHD).

Raw data are plotted over time. External events and the abstractions computed from the data are plotted as intervals above the data. BMT = bone marrow transplantation; B[0] = grade 0 bone marrow toxicity; B[I] = grade I bone marrow toxicity; B[II] = grade II bone marrow toxicity; B[III] = grade III bone marrow toxicity. Circles represent platelet counts; triangles represent granulocyte counts; arrows represent context intervals; solid lines represent abstraction intervals; the dotted line represents an event.

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Figure 3.
The Tzolkin temporal mediation architecture.

TM = temporal data maintenance module; TR = temporal reasoning module.

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Figure 4.
The Knowledge-Based Navigation of Abstractions for Visualization and Explanation (KNAVE) architecture.

Arrows indicate data or knowledge flow.

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Figure 5.
The interface to the interactive semantic exploration operators in the Knowledge-Based Navigation of Abstractions for Visualization and Explanation (KNAVE) architecture.

The seven browsers directly access the knowledge specific to the relevant clinical area. The display window reflects the results of a query to the temporal mediator, which accesses the patient's database. To facilitate browsing, the “derived-from“ (functional dependency) relation has been split into exploration instructions for “Derived-From Hierarchy” and “Supports Hierarchy.” CCTG = California Collaborative Trial Group; PAZ = prednisone-azathioprine.

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Figure 6.
Result of a “derived-from” exploration in the Knowledge-Based Navigation of Abstractions for Visualization and Explanation (KNAVE) architecturestarting from the abstractions shown inFigure 4bottom panel (top panel).

The user is exploring one of the intermediate abstractions (granulocyte state) from which the bone-marrow toxicity abstraction is derived and the raw data (granulocyte count) from which that intermediate abstraction is derived ( ). All abstractions are defined within the relevant clinical context (administration of the prednisone-azathioprine [PAZ] protocol) mentioned in the user's query ( ).

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