Publications by authors named "S Reed Plimpton"
Article Synopsis
- The study evaluates how effectively artificial intelligence (AI) can identify cancers that were missed by radiologists in routine screening mammograms.
- Utilizing a collection of data from 2010 to 2019, the research found that AI detected a significant portion of false negative cancers, identifying 54% in full-field digital mammography (FFDM) and 40% in digital breast tomosynthesis (DBT).
- The findings suggest AI identified these missed cancers much earlier than radiologists, indicating a need for further research on combining AI with radiologist expertise in real-world breast cancer screening.
The MolSSI Driver Interface (MDI) Project is an effort to simplify and standardize the process of enabling tight interoperability between independently developed code bases and is supported by numerous software packages across the domain of chemical physics. It enables a wide variety of use cases, including quantum mechanics/molecular mechanics, advanced sampling, path integral molecular dynamics, machine learning, ab initio molecular dynamics, etc. We describe two major developments within the MDI Project that provide novel solutions to key interoperability challenges.
View Article and Find Full Text PDFObjective: Assess the ongoing impact of COVID-19 on mental well-being of breast radiologists nationwide two years after the start of the pandemic and compared to early in the pandemic.
Methods: A 27-question survey was distributed from December 2021 to January 2022 to physician members of the Society of Breast Imaging. Psychological distress and anxiety scores were calculated, and factors associated with them were identified with a multivariate logistic model.
The topological constraints of nonconcatenated ring polymers force them to form compact loopy globular conformations with much lower entropy than unconstrained ideal rings. The closed-loop structure of ring polymers also enables them to be threaded by linear polymers in ring/linear blends, resulting in less compact ring conformations with higher entropy. This conformational entropy increase promotes mixing rings with linear polymers.
View Article and Find Full Text PDFObjective: Assess the impact of COVID-19 on patient-breast radiologist interactions and evaluate the relationship between safety measure-constrained communication and physician wellbeing.
Methods: A 41-question survey on the perceived effect of COVID-19 on patient care was distributed from June 2020 to September 2020 to members of the Society of Breast Imaging and the National Consortium of Breast Centers. Non-radiologists and international members were excluded.