United States Department of Veterans Affairs

Type

Government

Country

United States

US

ROR

05rsv9s98

not unique to one org

OpenAlex

I1322918889

the anchor

Documents

34

through any edge

Papers

34

authorship edges

Awards made

Named as funder

Papers

Documents in the 44B Library with United States Department of Veterans Affairs on the authorship, newest first.

2026-04-17 · 11 authors here

Rapid Evaluation of Artificial Intelligence Technology Used for Ambient Dictation in Primary Care: Comparing the Quality of Documentation of Artificial Intelligence–Generated and Human-Produced Clinical Notes

2026-04-09 · 25 authors here

Increasing value in the Veterans Affairs Healthcare System (VA) with precision health: a continuing landmark collaboration with the Department of Energy

2026-01-01 · 4 authors here

Additional file 5 of Utilizing large language models and natural language processing to classify ischemia status from cardiac stress tests in a large multicenter healthcare system

2026-01-01 · 4 authors here

Additional file 5 of Utilizing large language models and natural language processing to classify ischemia status from cardiac stress tests in a large multicenter healthcare system

2025-11-11 · 12 authors here

Using Generative Artificial Intelligence for Healthcare-Associated Infection Surveillance

2025-09-02 · 39 authors here

Pancancer outcome prediction via a unified weakly supervised deep learning model

2025-07-18 · 25 authors here

Unlocking efficiency in real-world collaborative studies: a multi-site international study with one-shot lossless GLMM algorithm

2025-07-18 · 15 authors here

A call for transdisciplinary trust research in the artificial intelligence era

2025-07-02 · 8 authors here

The Effect of Ambient Artificial Intelligence Scribes on Trainee Documentation Burden

2025-04-17 · 5 authors here

Machine-Learned Codes from EHR Data Predict Hard Outcomes Better than Human-Assigned ICD Codes

2025-03-27 · 20 authors here

Artificial intelligence-based virtual staining platform for identifying tumor-associated macrophages from hematoxylin and eosin-stained images

2025-02-07 · 7 authors here

Decoding substance use disorder severity from clinical notes using a large language model

2025-01-13 · 11 authors here

Use of AI in Family Medicine Publications: A Joint Editorial From Journal Editors

2025-01-01 · 11 authors here

Use of AI in family medicine publications: a joint editorial from journal editors

2025-01-01 · 7 authors here

The Present and Future of AI: Ethical Issues and Research Opportunities

2025-01-01 · 2 authors here

Advancing Cloud-Edge Applications Through Fog-Cloud Integration and Low-Latency Edge Solutions: A Narrative Case Study From Veterans Engineering

2024-09-09 · 27 authors here

Uptake of Cancer Genetic Services for Chatbot vs Standard-of-Care Delivery Models

2024-07-21 · 19 authors here

Clinical Relevance of Computationally Derived Tubular Features: Spatial Relationships and the Development of Tubulointerstitial Scarring in MCD/FSGS

2024-07-01 · 14 authors here

CohortFinder: an open-source tool for data-driven partitioning of digital pathology and imaging cohorts to yield robust machine-learning models

2024-06-19 · 7 authors here

Nurses' perceptions of the design, implementation, and adoption of machine learning clinical decision support: A descriptive qualitative study

2024-05-20 · 5 authors here

Comparing penalization methods for linear models on large observational health data

2024-03-08 · 11 authors here

A framework for inferring and analyzing pharmacotherapy treatment patterns

2024-02-22 · 23 authors here

To Do No Harm — and the Most Good — with AI in Health Care

2024-02-16 · 4 authors here

Use of noisy labels as weak learners to identify incompletely ascertainable outcomes: A Feasibility study with opioid-induced respiratory depression

2024-01-30 · 4 authors here

Use of Noisy Labels as Weak Learners to Identify Incompletely Ascertainable Outcomes: A Feasibility Study with Opioid-Induced Respiratory Depression

Showing 25 of 34 on record.

Funding

Read from the funding tables, never from the document count — that count includes authorship, so it ranks institutions, not funders.

Who funds this work

Funders named on the papers above. The record holds no recipient field, so this is reached through the documents themselves — and the two columns are two different claims, kept apart.

© 2026 NYSGPTLast Updated: August 5, 2026