Los Alamos National Laboratory

The need for uncertainty quantification in machine-assisted medical decision making

Edmon Begoli, Tanmoy Bhattacharya, Dimitri Kusnezov

2018 · 496 Zit.

So, are early career researchers the harbingers of change?

David Nicholas, Anthony Watkinson, Chérifa Boukacem‐Zeghmouri et al.

2019 · 91 Zit.

Correction for Vangay et al., “Microbiome Metadata Standards: Report of the National Microbiome Data Collaborative’s Workshop and Follow-On Activities”

Pajau Vangay, Josephine Burgin, Anjanette Johnston et al.

2021 · 8 Zit.

Deep learning uncertainty quantification for clinical text classification

Alina Peluso, Ioana Danciu, Hong‐Jun Yoon et al.

2023 · 5 Zit.

A landmark federal interagency collaboration to promote data science in health care: Million Veteran Program-Computational Health Analytics for Medical Precision to Improve Outcomes Now

Amy C. Justice, Benjamin H. McMahon, Ravi Madduri et al.

2024 · 3 Zit.

ASCR Workshop on In Situ Data Management

Tom Peterka, Deborah Bard, Janine Camille Bennett et al.

2019 · 3 Zit.

Uncertainty quantification by large language models

Dorianis M. Perez, Bryan E. Kaiser, Ismael Boureima

2025 · 1 Zit.

RCT Continuing Training (Q3, 2021) [Slides]

Justin Gillilan

2021 · 0 Zit.

The Future of Data

Suparna Bhattacharya, Thomas Coughlin, Luther H. Evans et al.

2025 · 0 Zit.

2021 Supercomputer Institute Outbrief [Slides]

Evan Donato

2021 · 0 Zit.

Increasing Value in the Veterans Affairs Healthcare System (VA) with Precision Health: A Continuing Landmark Collaboration with the Department of Energy

Amy C. Justice, Benjamin H. McMahon, Daniel Jacobson et al.

2025 · 0 Zit.

Confidence-weighted integration of human and machine judgments for superior decision-making

Felipe Yáñez, Xiaoliang Luo, Omar Valerio Minero et al.

2025 · 0 Zit.