activity
20172022
most citedPredicting Kovats Retention Indices Using Graph Neural Networks

2 citations · 5 across the 5 of their papers we have counts for

collaborators

6 papers

stat.ME20222 cited

Minimizing Uncertainty in Prevalence Estimates

Paul Patrone, Anthony Kearsley

Estimating prevalence, the fraction of a population with a certain medical condition, is fundamental to epidemiology. Traditional methods rely on classification of test samples tak…

stat.ME2022

Optimal Decision Theory for Diagnostic Testing: Minimizing Indeterminate Classes with Applications to Saliva-Based SARS-CoV-2 Antibody Assays

Paul N. Patrone, Prajakta Bedekar, Nora Pisanic +4

In diagnostic testing, establishing an indeterminate class is an effective way to identify samples that cannot be accurately classified. However, such approaches also make testing…

physics.chem-ph20202 cited

Predicting Kovats Retention Indices Using Graph Neural Networks

Chen Qu, Barry I. Schneider, Anthony J. Kearsley +2

The \kovats retention index is a dimensionless quantity that characterizes the rate at which a compound is processed through a gas chromatography column. This quantity is independe…

q-bio.QM20201 cited

Improving Baseline Subtraction for Increased Sensitivity of Quantitative PCR Measurements

Paul N. Patrone, Anthony J. Kearsley, Erica L. Romsos +1

Motivated by the current COVID-19 health-crisis, we examine the task of baseline subtraction for quantitative polymerase chain-reaction (qPCR) measurements. In particular, we prese…

physics.data-an2017

The Role of Data Analysis in Uncertainty Quantification: Case Studies for Materials Modeling

Paul N. Patrone, Anthony J. Kearsley, Andrew M. Dienstfrey

In computational materials science, mechanical properties are typically extracted from simulations by means of analysis routines that seek to mimic their experimental counterparts.…

math.AP2017

Diffusion-limited Reactions in Nanoscale Electronics

Ryan M. Evans, Arvind Balijepalli, Anthony J. Kearsley

A partial differential equation (PDE) was developed to describe time-dependent ligand-receptor interactions for applications in biosensing using field effect transistors (FET). The…