ACT-IAC Use Case Solutions Library
Got a Pain Point? Leverage Technology to Clear Mission Hurdles!
Now you can find others who have tackled similar challenges to learn how they might have approached the problem and, hopefully, solved it.
Submit a New Use Case or Solution for addition to the NUCSL
Displaying 169 - 192 of 307 cases
National Library of Medicine NLM-Chem: towards automatic chemical indexing in PubMed articles
Chemical indexing is part of the NLM’s MEDLINE citation indexing efforts for improving literature retrieval and information access. Currently, chemcial indexing is performed manually by expert indexers. To assist this time-consuming and resource-intensive process, we have developed NLM-Chem, an automatic tool for finding chemical names in the biomedical literature using advanced natural…
National Library of Medicine NLM-Gene: towards automatic gene indexing in PubMed articles
Gene indexing is part of the NLM’s MEDLINE citation indexing efforts for improving literature retrieval and information access. Currently, gene indexing is performed manually by expert indexers. To assist this time-consuming and resource- intensive process, we have developed NLM-Gene, an automatic tool for finding gene names in the biomedical literature using advanced natural language…
NIH Grants Virtual Assistant
Chat Bot to assist users in finding grant related information via OER resources
NLP FOR FOREIGN ASSISTANCE APPROPRIATIONS ANALYSIS
Natural language processing application to automate and streamline the extraction of earmarks and directives from the annual appropriations bill to facilitate the Department’s adherence to congressional direction.
NLP TO PULL KEY INFORMATION FROM UNSTRUCTURED TEXT
Use natural language processing to extract information from document text to help summarize and allow for analysis more efficiently than manual methods.
NN Radiation
Developing fast and accurate NN LW- and SW radiations for GFS and GEFS. NN LW- and SW radiations have been successfully developed for previous version of GFS, see: doi: 10.1175/2009MWR3149.1 and the stability and robustness of the approach used was demonstrated, see: https://arxiv.org/ftp/arxiv/papers/2103/2103.07024.pdf NN…
NN training software for the new generation of NCEP models
Optimize NCEP EMC Training and Validation System for efficient handling of high spatial resolution model data produced by the new generation of the NCEP operational models
Nuclear-Renewable-Storage Digital Twin: Enhancing Design, Dispatch, and Cyber Response of Integrated Energy Systems
This project will develop a learning-based and digital twin enabled modeling and simulation framework for economic and resilient real-time decision-making of physics- informed integrated energy systems (IES) operation. High-fidelity physics models will be linked with large-scale grid monitoring data to provide real-time updates of IES states, predictive control systems, and optimized power…
Objective-Driven Data Reduction for Scientific Workflows
This project aims to develop theories and algorithms for objective-driven reduction of scientific data in workflows that are composed of various models, including data- driven AI models
Open-Source High-Fidelity Aggregate Composite Load Models of Emerging Load Behaviors for Large-Scale Analysis (GMLC 0064)
1. Machine learning methods such as cross-correlation, random forest, regression tree and transfer learning are used to estimate the load composition data and motor protection profiles for different climante regions in the Western US
2. Deep learning algorithm is appplied to calibrate the parameters of WECC
composite load model to match the responses with detailed feeder model
Open-source News Aggregation
The platform enables users to make better decisions faster by identifying and forecasting emerging events on a global scale to mitigate risk, recognize threats, greatly enhance indications and warnings, and provide predictive intelligence capabilities. The artificial intelligence / machine learning models enable rapid access to automated intelligence assessments by fusing, processing,…
Operational water supply forecasting for western US rivers
Western US water management is underpinned by forecasts of spring-summer river flow volumes made using operational hydrologic models. The USDA Natural Resources Conservation Service (NRCS) National Water and Climate Center operates the largest such forecast system regionally, carrying on a nearly century-old tradition. The NWCC recently developed a next-generation prototype for generating such…
Opioid Data Warehouse Term Identification and Novel Synthetic Opioid Detection and Evaluation Analytics
The Term Identification and Novel Synthetic Opioid Detection and Evaluation Analytics use publicly available social media and forensic chemistry data to identify novel referents to drug products in social media text. It uses the FastText library to create vector models of each known NSO-related term in a large social media corpus, and provides users with similarity scores and expected…
Pangolin lineage classifications to support accessing and analysis of SARS-CoV-2 sequence data.
The Pango nomenclature, called Pango lineages, is being used by researchers and public health agencies worldwide to track the transmission and spread of SARS-CoV-2, including variants of concern. The requirements for running the tool include having conda on a MacOS or Linux system, and the FASTA-formated sequence data. There are 2 methods for lineage assignment with Pango; within NCBI Virus we…
Passive acoustic analysis using ML in Cook Inlet, AK
Passive acoustic data is analyzed for detection of beluga whales and classification of the different signals emitted by these species. Detection and classification are done with an ensemble of 4 CNN models and weighted scoring developed in collaboration with Microsoft. Results are being used to inform seasonal distribution, habitat use, and impact from anthropogenic disturbance within Cook…
Passive Strain Measurements for Experiments in Radiation Environments
This project will develop passive instrumentation to determine permanent strains induced by irradiation and extract critical parameters using modeling and simulation as well as machine learning algorithms. An irradiation experiment will be conducted that will benefit from engineered anisotropic materials and characterize the directional deformation in response to neutron radiation. The…
Person-level disambiguation for PubMed authors and NIH grant applicants
High-quality disambiguation is required to correctly link researchers to their grants and outputs including articles, patents, and clinical trials. The NIH Office of Portfolio Analysis developed a disambiguation solution that used article level metadata to assign 24.5M unique papers from the PubMed database to 16.0M unique author names, then used a novel neural network model trained on ORCID…
Picky
Using CNN to pick out objects of a particular size from sides scan imagery. Presents users with a probability that allows for automation of contact picking in the field. Side scan imagery is simple one channel intensity image which lends itself well to basic CNN techniques.
PMU-Based Data Analytics Using Digital Twin Phasor Analytics Software
Explore the use of big data, artificial intelligence (AI), and machine learning technology and tools on phasor measurement unit (PMU) data to identify and improve existing knowledge, and to discover new insights and tools for better grid operation and management.
Predicting hospitalization and corticosteroid use as a surrogate for IBD flares
This work examines data from 20,368 Veterans Health Administration (VHA) patients with an irritable bowel disease (IBD) diagnosis between 2002 and 2009. Longitudinal labs and associated predictors were used in random forest models to predict hospitalizations and steroid usage as a surrogate for IBD Flares.
Prediction of health outcomes, including suicide death, opioid overdose, and decompensated outcomes of chronic diseases.
Using electronic health records (EHR) (both structured and unstructured data) as inputs, this tool outputs deep phenotypes and predictions of health outcomes including suicide death, opioid overdose, and decompensated outcomes of chronic diseases.
Prediction of Veterans Suicidal Ideation following Transition from Military Service
Machine learning is used to identify predictors of veterans suicidal ideation. The relevant data come from a web-based survey of veterans experiences within three months of separation and every six months after for the first three years after leaving military service.
Predictive Intelligence - Incident Assignment for Quality Service Center (QSC).
Predictive Intelligence (PI) is used for incident assignment within the Quality Service Center (QSC). The solution runs on incidents created from the ServiceNow Service Portal (https://cmsqualitysupport.servicenowservices.com/sp_ess). The solution analyzes the short description provided by the end user in order to find key…
Priority Score Model - ranks providers within the Fraud Prevention System using logistic regression based on program integrity guidelines.
Inputs - Medicare Claims data, Targeted Probe and Educate (TPE) Data, Jurisdiction information
Output - ranks providers within the FPS system using logistic regression based on program integrity guidelines.