Registered Data

[00794] Mathematical Modelling and Disease

  • Session Time & Room : 2E (Aug.22, 17:40-19:20) @A512
  • Type : Proposal of Minisymposium
  • Abstract : Mathematical modeling and estimation strategies are especially useful in the fight against disease be it through diagnosis, prediction, or management. Examples include analyzing medical device performance and providing simulation, constructing probabilistic/stochastic models that define classification strategies that in turn guide diagnostic testing. In this minisymposium, these themes will be investigated through specific ‘real world’ examples emphasizing metrology and the importance of measurement science in using mathematics to treat disease.
  • Organizer(s) : Anthony Kearsley, Luis Melara
  • Classification : 92-10, 92-08, 92C75
  • Minisymposium Program :
    • 00794 (1/1) : 2E @A512 [Chair: Luis Melara]
      • [01627] Transboundary management of ecological systems with applications to diseases
        • Format : Talk at Waseda University
        • Author(s) :
          • Julie Blackwood (Williams College)
        • Abstract : Human migration and infectious diseases often span multiple administrative jurisdictions that might have different systems of government and management objectives. I'll introduce two examples in which spatial coordination may be critical for disease control. First, I’ll demonstrate that spatial interactions of vampire bats likely play a key role in driving rabies persistence. Second, I’ll describe a more general infectious disease in humans and show that successful management may depend on the actions of multiple managers.
      • [04446] Separating Populations in Flow Cytometry Experiments: A Probabilistic Approach
        • Format : Talk at Waseda University
        • Author(s) :
          • Danielle J Middlebrooks (National Institute of Standards and Technology)
        • Abstract : Flow cytometry (FC) is used in many areas of clinical testing, measuring cell characteristics of roughly one million cells. Data analysis is critical for interpreting FC measurements, but traditional techniques are often time-consuming and subjective. Our methodology identifies an unknown population by constructing probability density functions of specific biomarker expression levels in a sample. Once we estimate the unknown distribution, we compute the relative fraction of the unknown population and estimates of the uncertainty.
      • [04840] Case Studies in Modeling and Optimization for Diagnostics
        • Format : Talk at Waseda University
        • Author(s) :
          • Prajakta Purushottam Bedekar (National Institute of Standards and Technology)
          • Paul Patrone (National Institute of Standards and Technology)
          • Anthony Kearsley (National Institute of Standards and Technology)
        • Abstract : We demonstrate that modeling and optimization are crucial tools for interpretation of diagnostic measurements through case studies. First we model the errors in dilution and find a best-fit to minimize variability of biological antibody measurements, enabling us to compare results across experiments. Secondly, we use optimal decision theory to develop a time-dependent, probabilistic classification and adaptive prevalence estimation scheme using antibody testing measurements. We demonstrate the results by using SARS-CoV-2 datasets.
      • [03298] Optimal Bandwith Selection in Bio-FET Measurements
        • Format : Talk at Waseda University
        • Author(s) :
          • Luis Melara (Shippensburg University)
        • Abstract : The use of stochastic regression to separate signal from noise produced by Bio-FETs will be discussed in this talk. The noise realized by BioFETs interferes with quantitative and qualitative analysis, thus determining optimal bandwidth associated with experimental Bio-FET data measurements is an important task. Presented results suggest consistent across aspect rations and a choice of stochastic regression kernel function and yield what appear to be good results.