Enhancing influenza A risk assessment rubrics: leveraging predictive correlates and machine learning from in vivo experiments.
The Pathogenesis Laboratory Team (Immunology and Pathogenesis Branch, Influenza Division, NCIRD) routinely performs influenza A virus (IAV) risk assessment studies in the ferret a…
Data Standardization with LLM
The purpose of this project is to enhance data standardization efforts by leveraging large language models. to improve data cleaning and standardization processes, ultimately enha…
Using Databricks Genie for Routine Immunization Data Insights
The volume of immunization data reported quarterly is approximately 5 billion records. Analyzing this data to gather high-level insights requires complex coding and manipulation.…
Beryllium exposure reconstruction
Using machine learning to extract information about job title and task and assign relevant exposure codes.
Mining.AI
Mining.AI is an innovative initiative led by a small team at NIOSH tasked to develop a domain-specific generative LLM AI platform focused on improving health and safety in the min…
Deep Research for Public Health
Public health agencies like the CDC face challenges in efficiently processing large volumes of complex information, conducting evidence-based research, and producing timely, high-…
CDER Publications
Inefficient manual curation and categorization of publications by CDER authors. It aims to automate the process of organizing publications by focus areas for data call responses a…
CoreDF
Current nonclinical review processes require manual extraction and analysis of sponsor findings from lengthy PDF study reports, creating inefficiencies in data quality assessment…
AI-Enhanced FDA Regulated Commodity Consumption Pattern Analysis
Traditional analytical methods for determining consumption patterns of FDA-regulated commodities are limited in scope and processing speed which hinders comprehensive market surve…
NCI-DOE Collaboration, MOSSAIC project (Modeling Outcomes using Surveillance Data and Scalable AI for Cancer)
MOSSAIC applies deep learning natural language processing (NLP) and foundation models to population-based cancer data collected by NCI's Surveillance, Epidemiology, and End Result…
TB Case Browser Image Text Detection
Without OCR technology, validation of text on images is manually intensive and, without proper controls, can create the risk of sensitive information coming into the system.
Aivia
Provides machine-learning-based object classification in microscopy applications
Alphafold
Prediction of atomic models from CryoEM specimens.
cryoDGRN
Prediction of protein flexibility and variability
crYOLO
Automated screening of CryoEM specimens
CryoSPARC
Prediction of protein flexibility and variability
DeepEMhancer
Automated screening of CryoEM specimens
FIJI
Provides machine-learning-based object classification in microscopy applications
Imaris
Provides machine-learning-based object classification in microscopy applications
ModelAngelo
Prediction of atomic models from CryoEM specimens.
Pangolin Lineage Classification of SARS-CoV-2 Genome Sequences
Process a high volume of sequence data in real time to identify meaningful mutational patterns while minimizing the need for human effort.
Ptolemy
Automated screening of CryoEM specimens
TB DEPOT (Tuberculosis Data Exploration Portal)
There was a lack of deidentified, multidimensional tuberculosis socioeconomic, clinical, imaging, and pathogen genomic data available for researchers to use in developing models a…
TB Portals Outlier Detection Lambda Function
The quality of chest X-ray (CXR) images uploaded by TB Portals Program partners varied significantly, and as the scale of images increased, NIAID needed a way to identify outliers…