Please find my Google Scholar profile here
A pdf copy of my CV is available here.
Peer Reviewed Publications
- Pitts, A.J. & Fowler, C.R. (2024). Comparison
of open-source software for producing directed acyclic graphs.
Journal of Causal Inference. vol. 12, no. 1, 2024,
pp. 20230031. https://doi.org/10.1515/jci-2023-0031
- Singh, T., Pitts, A.J., Miles, C.H., Ing, C.H.
(2023). Anesthetic Exposure During Early Childhood and
Neurodevelopmental Outcomes: Our Current Understanding. Current
Anesthesiology Reports https://doi.org/10.1007/s40140-023-00592-y
- Lawlor, M.K., Ng, V., Ahmed, S., Dershowitz, L., Brener, M.I.,
Kampaktsis, P., Pitts, A., Vahl, T., Nazif, T., Leon,
M. and George, I. (2023). Baseline characteristics and clinical outcomes
of a tricuspid regurgitation referral population. The American
Journal of Cardiology, 196, (pp.22-30).
- Lawlor, M., Ng, V.G., Ahmed, S., Dershowitz, L., Brener, M.,
Kampaktsis, P., Pitts, A., Vahl III, T.P., Nazif, T.,
Leon, M.B. and George, I., 2023. Right Atrial Pressure in Pulmonary
Hypertension Assessment in Tricuspid Regurgitation. Journal of the
American College of Cardiology, 81(8_Supplement),
pp.1970-1970.
- Pitts, A., & Rivas, P., “Finding Time Series
Breakpoints with Fully Connected Neural Networks”, Int’l Conf.
Artificial Intelligence CSREA Press. 2019. p.352-357. ISBN:
1-60132-501-0.
Select Works in Progress
- Duong, N.Q., Pitts, A.J., Kim, S. & Miles, C.H.
Sensitivity analysis for transportability in multi-study, multi-outcome
settings arXiv preprint
arXiv:2301.02904 (2023).
- Pitts, A.J., Yomogida, M., Aidala, A., Gelman, A.,
Chen, Q. Inference of health outcomes among patients with HIV during
COVID-19 pandemic: using MRP model to improve survey representativeness.
(in preparation)
Other Projects
Association of Bayesian Go/No-Go Design in Early Oncology
Studies
This is a project completed during my internship at Bristol Myers
Squibb. It is a shiny
app that explores how the Simon’s Two-Phase Design can be adapted to
a dual criterion Bayesian design.
Dose Escalation Methods
This is the second project that I completed during my time at Bristol
Myers Squibb. I developed a shiny app
that compares 11 different dose escalation methods through user
specified simulations. It also compares decision tables for the methods
that can be summarized into one.
Missing Data in Cancer Studies.
View an interactive visualization of how missing data introduce bias
in my Shiny
App!