10 papers
Explicit Solutions in a Probabilistic Cellular Automaton Model for Self-Assembled Monolayer Degradation
Wes Caldwell, Ryan Evans, Jacob Majikes +1
Self-assembled monolayers (SAMs), formed by the adsorption of a monomolecular layer of adsorbate onto a surface, have emerged as leading candidates for plat- forms for electrochemi…
Trojans in Artificial Intelligence (TrojAI) Final Report
Kristopher W. Reese, Taylor Kulp-McDowall, Michael Majurski +68
The Intelligence Advanced Research Projects Activity (IARPA) launched the TrojAI program to confront an emerging vulnerability in modern artificial intelligence: the threat of AI T…
Wafer-Level Prototyping Tools for CMOS Bioelectronic Sensors
Advait Madhavan, Ruohong Shi, Alokik Kanwal +5
Integrating biology with complementary metal-oxide-semiconductor (CMOS) sensors can enable highly parallel measurements with minimal parasitic effects, significantly enhancing sens…
Probabilistic Modeling of Antibody Kinetics Post Infection and Vaccination: A Markov Chain Approach
Rayanne A. Luke, Prajakta Bedekar, Lyndsey M. Muehling +7
Understanding the dynamics of antibody levels is crucial for characterizing the time-dependent response to immune events: either infections or vaccinations. The sequence and timing…
Inequalities for Optimization of Classification Algorithms: A Perspective Motivated by Diagnostic Testing
Paul N. Patrone, Anthony J. Kearsley
Motivated by canonical problems in medical diagnostics, we propose and study properties of an objective function that uniformly bounds uncertainties in quantities of interest extra…
Probabilistic Consistency in Machine Learning and Its Connection to Uncertainty Quantification
Paul Patrone, Anthony Kearsley
Machine learning (ML) is often viewed as a powerful data analysis tool that is easy to learn because of its black-box nature. Yet this very nature also makes it difficult to quanti…
Per-event Uncertainty Quantification for Flow Cytometry using Calibration Beads
Prajakta Bedekar, Megan A. Catterton, Matthew DiSalvo +3
Flow cytometry measurements are widely used in diagnostics and medical decision making. Incomplete understanding of sources of measurement uncertainty can make it difficult to dist…
Uncertainty Quantification of Antibody Measurements: Physical Principles and Implications for Standardization
Paul N. Patrone, Lili Wang, Sheng Lin-Gibson +1
Harmonizing serology measurements is critical for identifying reference materials that permit standardization and comparison of results across different diagnostic platforms. Howev…
Analysis of Diagnostics (Part II): Prevalence, Linear Independence, and Unsupervised Learning
Paul N. Patrone, Raquel A. Binder, Catherine S. Forconi +2
This is the second manuscript in a two-part series that uses diagnostic testing to understand the connection between prevalence (i.e. number of elements in a class), uncertainty qu…
Prevalence estimation methods for time-dependent antibody kinetics of infected and vaccinated individuals: a graph-theoretic approach
Prajakta Bedekar, Rayanne A. Luke, Anthony J. Kearsley
Immune events such as infection, vaccination, and a combination of the two result in distinct time-dependent antibody responses in affected individuals. These responses and event p…