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Filtering by: Contributor National Institutes of Health grant #1R01AT010413-01 Creator Nirmish Shah Keyword Gaussian naive Bayes Resource type Dataset Subject Chronic pain

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1. 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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1. 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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1. Supplementary data for "Can subjective pain be inferred from objective physiological data? Evidence from patients with sickle cell disease" (PLOS CB, 2021)