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Temporal Case-Based Reasoning for Personalized Hypertensive Treatment

[+] Author Affiliations
Niloofar Jalali, Ibrahim Zeid, Sagar Kamarthi

Northeastern University, Boston, MA

Stephen Agboola, Kamal Jethwani

Harvad Medical School, Boston, MA

Paper No. IMECE2016-67066, pp. V014T07A018; 6 pages
doi:10.1115/IMECE2016-67066
From:
  • ASME 2016 International Mechanical Engineering Congress and Exposition
  • Volume 14: Emerging Technologies; Materials: Genetics to Structures; Safety Engineering and Risk Analysis
  • Phoenix, Arizona, USA, November 11–17, 2016
  • Conference Sponsors: ASME
  • ISBN: 978-0-7918-5068-8
  • Copyright © 2016 by ASME

abstract

Most of the current problems can be solved by referring to the solutions of the previous problems. Case Based reasoning (CBR) is one of the methods that solves a problem by retrieving the similar problems from the past and adapting the solutions of the past problems to solve the new problem. Recent studies that apply CBR include time as a parameter to retrieve most effective solutions that vary with time. This approach is more helpful in healthcare area in which one needs to look at historical evidence to find an accurate diagnostic or treatment regime. Hence, in this study, a time-based CBR is applied to track the outcomes of the drug therapy on hypertensive patients and find the most effective drug as a prescription. Initially, episodes in each patient’s medical records are chronologically ordered such that the oldest episode is placed first in the episode sequence and the latest episode is placed the last. It is assumed that the first episode of each patient is the first instance of diagnose; so when a new patient comes for checkup, his/her state (health condition) is compared with the initial state of the past patients. Therefore, the retrieval process calculates the similarity between the new patient’s current state and the most similar patients at their first episodes in the patient records. Due to the diversity of therapies for matching patients, the best treatment couldn’t be determined without knowing the efficacy of the different treatments. Therefore, the subsequent episodes of matching patients are examined to find the best treatment for the new patient. This might even require using a combination of treatments from all matching patients to find a good treatment for the new patient.

After the treatment is defined for the first visit, the record of the new patient is stored in the library for future case retrieval. This method is a novel approach to personalized treatment of patients having chronic disease by tracking the medical records past patients over a long period of time.

The current approach for treating the hypertensive patients uses evidence-based guidelines for managing the disease. However, this approach is more general and doesn’t take into account all the patient characteristics such as lab results and physical examination parameters. In the current approach the similarity between patients can’t be leveraged; the change of the treatment regime is based only on the risk parameter. However, in this method several parameters are being checked for efficiency of the medication. In contrast, the proposed CBR-based method personalizes the treatment based on what worked well for similar patients.

In this paper, the clinical records of hypertensive patients are provided by a Boston based hospital. The preliminary results confirm that the proposed approach will give good recommendation for hypertension treatment.

Copyright © 2016 by ASME

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