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Case-Based Reasoning in the Care of Alzheimer’s Disease Patients

Cindy MarlingContact Information and Peter WhitehouseContact Information

(3)  School of Electrical Engineering and Computer Science, Ohio University, Athens, Ohio 45701, USA
(4)  University Alzheimer Center and School of Medicine, Case Western Reserve University, Cleveland, Ohio 44106, USA
Abstract
Planning the ongoing care of Alzheimer’s Disease (AD) patients is a complex task, marked by cases that change over time, multiple perspectives, and ethical issues. Geriatric interdisciplinary teams of physicians, nurses and social workers currently plan this care without computer assistance. Although AD is incurable, interventions are planned to improve the quality of life for patients and their families. Much of the reasoning involved is case-based, as clinicians look to case histories to learn which interventions are effective, to document clinical findings, and to train future health care professionals.
There is great variability among AD patients, and within the same patient over time. AD is not yet well enough understood for universally effective treatments to be available. The case-based reasoning (CBR) research paradigm complements the medical research approach of finding treatments effective for all patients by matching patients to treatments that were effective for similar patients in the past.
The Auguste Project is an effort to provide decision support for planning the ongoing care of AD patients, using CBR and other thought processes natural to members of geriatric interdisciplinary teams. System prototypes are used to explore the reasoning processes involved and to provide the forerunners of practical clinical tools. The first system prototype has just been completed. This prototype supports the decision to prescribe neuroleptic drugs to AD patients with behavioral problems. It uses CBR to determine if a neuroleptic drug should be prescribed and rule-based reasoning to select one of five approved neuroleptic drugs for a patient. The first system prototype serves as proof of concept that CBR is useful for planning ongoing care for AD patients. Additional prototypes are planned to explore the research issues raised.

Contact Information Cindy Marling
Email: marling@ohio.edu

Contact Information Peter Whitehouse
Email: pjw3@po.cwru.edu
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Referenced by
3 newer articles

  1. Chun, Se-Chul (2008) Data mining technique for medical informatics: detecting gastric cancer using case-based reasoning and single nucleotide polymorphisms. Expert Systems 25(2)
    [CrossRef]
  2. Begum, Shahina (2009) A CASE-BASED DECISION SUPPORT SYSTEM FOR INDIVIDUAL STRESS DIAGNOSIS USING FUZZY SIMILARITY MATCHING. Computational Intelligence 25(3)
    [CrossRef]
  3. Park, Yoon-Joo (2006) New knowledge extraction technique using probability for case-based reasoning: application to medical diagnosis. Expert Systems 23(1)
    [CrossRef]
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