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Filtering by: Contributor National Institutes of Health grant #1R01AT010413-01 Keyword Gaussian naive Bayes Resource type Dataset Subject Mathematical models

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Supplementary data for "Can subjective pain be inferred from objective physiological data? Evidence from patients with sickle cell disease" (PLOS CB, 2021)

Description:

Patients with sickle cell disease (SCD) experience lifelong struggles with both chronic and acute pain, often requiring medical intervention. Pain can be managed with medications, but dosages must balance the goal of pain mitigation against the risks of tolerance, addiction and other adverse effects. Setting appropriate dosages requires knowledge of...

Keyword:

subjective pain, probabilistic model, mathematical model, SCD, sickle cell disease, hidden Markov model, and Gaussian naive Bayes

Subject:

Hidden Markov models, Chronic pain, Mathematical models, and Sickle cell anemia

Creator:

Mark J. Panaggio, Tanvi Banerjee, Daniel M. Abrams, Fan Yang, and Nirmish Shah

Contributor:

National Institutes of Health grant #1R01AT010413-01

Owner:

Daniel M Abrams

Publisher:

Abrams research group

Language:

English

Date Uploaded:

12/22/2020

Date Modified:

01/26/2021

Date Created:

2020-12-22

Resource Type:

Dataset

Alternate Identifier:

DOI (to come)

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Supplementary data for "Can subjective pain be inferred from objective physiological data? Evidence from patients with sickle cell disease" (PLOS CB, 2021)

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