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48,453 grants matching “machine learning”
Biochemistry of Energy-Dependent (Intracellular) Protein Degradation
$926,883Michael Maurizi · Division Of Basic Sciences - Nci · Z01 · FY2008 · CA
Bilateral Acoustic Sensing and Automated Breathing Segmentation for Remote Monitoring of Patients with COPD: A Longitudinal Study
$926,715Lloyd Emokpae · Lasarrus Clinic And Research Center, Inc. · R44 · FY2025 · HL
Early detection and monitoring of Alzheimers Disease and Related Dementias using non-semantic linguistic and acoustic features of speech derived from hearing aids
$926,545Brian John Bischoff · Headwaters Innovation, Inc. · R44 · FY2025 · AG
Extended preservation of human livers: a nature inspired, high subzero controlled, limited freezing approach
$926,465Michael John Taylor · Sylvatica Biotech, Inc. · R44 · FY2023 · DK
Human Tumor Atlas Network: Data Coordinating Center Supplement
$926,364Ethan Cerami · Dana-Farber Cancer Inst · U24 · FY2020 · CA
Collaborative Research: SCH:Personalized Watch-based Fall Risk Analysis and Detection with Cross Modal Learning
$926,249Anne H Ngu · Texas State University - San Marcos · · FY2021 · ENG
BRAIN INITIATIVE RESOURCE: DEVELOPMENT OF A HUMAN NEUROELECTROMAGNETIC DATA ARCHIVE AND TOOLS RESOURCE (NEMAR)
$926,107Scott Makeig · University Of California, San Diego · R24 · FY2019 · MH
CRISP Type 2: Collaborative Research: Towards Resilient Smart Cities
$926,000Narayan Mandayam · Rutgers University New Brunswick · · FY2016 · CSE
SBIR Phase II: A Multi-Modality Sensing Approach for the Objective Assessment of Agitation and Sedation
$925,978Behnood Gholami · Autonomous Healthcare Inc · · FY2015 · TIP
Solving Sepsis: Early Identification and Prompt Management Using Machine Learning
$925,681Manesh R Patel · Cohere-Med, Inc. · R42 · FY2024 · GM
Altered metabolism and machine learning for pancreatic cancer early detection
$925,639Brian Matthew Wolpin · Dana-Farber Cancer Inst · U01 · FY2022 · CA
BEST CARE for Recurrent NMIBC: BladdEr-Sparing Therapy and Cystectomy As TREatments
$925,430John L. Gore · University Of Washington · R01 · FY2025 · CA
COPD(GENE): TASK B: "STEWARDSHIP OF BIOSPECIMEN AND DATA REPOSITORIES"
$925,355James D Crapo · National Jewish Health · N01 · FY2023 · HL
Machine learning methods in data science for clinical prediction and characterization
$925,072Jeremy Weiss · National Library Of Medicine · ZIA · FY2023 · LM
Collaborative Research: RECODE: Directing and Controlling Cardiac Differentiation Through Cellular and Microenvironmental Manipulation and Application of Machine-Learning
$924,660Elizabeth A Lipke · Auburn University · · FY2021 · ENG
EnCoRe MOMS: Engaging Communities to Reduce Morbidity from Maternal Sepsis
$924,374Dena Goffman · Columbia University Health Sciences · UH3 · FY2025 · HD
Discovering Chemical Activity Networks-Predicting Bioactivity Based on Structure
$924,091Robert L Tanguay · Oregon State University · R35 · FY2024 · ES
Clinical Research Design, Epidemiology and Biostatistics Core
$924,077Susan L. Santangelo · Mainehealth · U54 · FY2020 · GM
Use of Next-Gen Sequencing to Identify Genetic Variants that Influence compulsive Oxycodone Intake in Outbred Rats
$924,074Olivier George · University Of California, San Diego · U01 · FY2023 · DA
DECISION SUPPORT SYSTEMS FOR WILDLAND FIRE BEHAVIOR ARE ESSENTIAL FOR EFFECTIVE AND EFFICIENT WILDLAND FIRE RISK ASSESSMENT AND FIREFIGHTING. TOGETHER WITH THE CENTER OF EXCELLENCE FOR ADVANCED TECHNOLOGY AERIAL FIREFIGHTING IN RIFLE COLORADO WE ARE DEVELOPING A WILDLAND FIRE PREDICTION SYSTEM FOR THE STATE OF COLORADO. THE MISSION OF THE CENTER OF EXCELLENCE IS: "TO PROTECT CITIZENS LAND AND RESOURCES IN COLORADO THE CENTER OF EXCELLENCE WILL RESEARCH TEST AND EVALUATE EXISTING AND NEW TECHNOLOGIES THAT SUPPORT SUSTAINABLE EFFECTIVE AND EFFICIENT AERIAL FIREFIGHTING TECHNIQUES." THE WILDLAND FIRE PREDICTION SYSTEM IS BASED ON THE NATIONAL CENTER OF ATMOSPHERIC RESEARCH'S COUPLED ATMOSPHERE WILDLAND FIRE ENVIRONMENT (CAWFE) MODEL AND THE WEATHER RESEARCH AND FORECASTING - FIRE (WRF-FIRE) MODEL. WRF-FIRE IS AN EXTENSION OF THE WIDELY USED COMMUNITY NUMERICAL WEATHER PREDICTION MODEL WRF. IN ADDITION TO ATMOSPHERIC CONDITIONS AND FUEL TYPE FUEL MOISTURE CONTENT (FMC) IS A CRITICAL FACTOR CONTROLLING THE RATE OF SPREAD AND HEAT RELEASE FROM WILDLAND FIRES. PREVIOUS STUDIES HAVE SHOWN THAT THE INTENSITY AND FREQUENCY OF OCCURRENCE OF LARGE FIRES ARE MORE HIGHLY CORRELATED TO REDUCED VEGETATION MOISTURE THAN INCREASED AIR OR FUEL TEMPERATURE. ACCURATE INFORMATION ABOUT FMC IS THEREFORE ESSENTIAL FOR MORE ACCURATE WILDLAND FIRE SPREAD PREDICTION. CURRENTLY THE COUPLED OPERATIONAL WILDLAND FIRE PREDICTION SYSTEM IS AT TECHNICAL READINESS LEVEL (TRL) 4. THE COUPLED ATMOSPHERE- WILDLAND FIRE SPREAD MODEL HAS BEEN IMPLEMENTED IN THE PROTOTYPE OPERATIONAL SYSTEM AND THE AVAILABLE RELEVANT DATA SETS ARE ASSIMILATED IN THE OPERATIONAL FORECASTING PROCESS. THE SYSTEM IS UNDERGOING TESTING IN REAL TIME AT THE SCALE OF THE STATE OF COLORADO AS REQUIRED. THE FUEL DATA COMPONENT OF THE OPERATIONAL SYSTEM IS AT THE TRL 2. A SIMPLE FUEL MODEL (ANDERSON 1982) HAS BEEN IMPLEMENTED. THIS MODEL DOES NOT ALLOW FOR THE OBSERVED VARIABILITY IN FMC. A MORE ADVANCED (I.E. SCOTT AND BURGAN 2005) FUEL MODEL IS BEING IMPLEMENTED. HOWEVER A DYNAMIC GRIDDED FMC DATA SET THAT CAN BE ASSIMILATED IN REAL-TIME IN THE OPERATIONAL SYSTEM DOES NOT EXIST. PRESENTLY THE NATIONAL FUEL MOISTURE DATABASE (AVAILABLE VIA THE WILDLAND FIRE ASSESSMENT SYSTEM) PROVIDES CONTINUOUSLY UPDATED INFORMATION ABOUT FMC BASED ON SURFACE OBSERVATIONS FROM REMOTE AUTOMATED WEATHER STATIONS (RAWS). TO PROVIDE FMC DATA AT ANY LOCATION IN THE CONUS MEASUREMENTS ARE INTERPOLATED USING AN INVERSE DISTANCE SQUARED INTERPOLATION. HOWEVER CONSIDERING THE SPARSE SPATIAL DISTRIBUTION OF RAWS ANY INTERPOLATION METHOD CAN RESULT IN LARGE ERRORS IN SPATIAL FMC DISTRIBUTION. WE THEREFORE PROPOSE TO USE SATELLITE REMOTE SENSING OBSERVATIONS TO DEVELOP MORE ACCURATE GRIDDED DYNAMIC REAL-TIME FMC DATABASE PRODUCT FOR USE WITH THE DYNAMIC SCOTT AND BURGAN (2005) FIRE BEHAVIOR FUEL MODELS. BY COMBINING VEGETATION INDEX PRODUCTS FROM THE POLAR ORBITING MODIS INSTRUMENTS WE WILL DEVELOP A HIGH TEMPORAL AND SPATIAL RESOLUTION FMC PRODUCT. THE VEGETATION INDICES WILL BE COMBINED USING MACHINE LEARNING ALGORITHMS AND CALIBRATED USING SURFACE RAWS OBSERVATIONS TO PRODUCE A BEST ESTIMATE OF THE DEAD AND LIVE FUEL MOISTURE CONTENT. THE DEAD AND LIVE FMC WILL BE COMBINED TO DERIVE TOTAL FUEL MOISTURE CONTENT IN THE WIDELY USED ROTHERMEL (1972) FIRE SPREAD MODEL. THE USE OF THE NEW GRIDDED FMC DATABASE WILL BE DEMONSTRATED IN OUR WRF-FIRE COUPLED ATMOSPHERE WILDLAND FIRE PREDICTION MODEL. MORE ACCURATE ACCOUNTING FOR LIVE AND DEAD FMC THROUGH ASSIMILATION OF SATELLITE OBSERVATIONS WILL RESULT IN MORE REALISTIC DYNAMIC REPRESENTATION OF FUEL HETEROGENEITY AND IN IMPROVED ACCURACY OF WILDLAND FIRE SPREAD PREDICTION. THE EFFECTIVENESS OF THE COUPLED ATMOSPHERE WILDLAND FIRE SPREAD PREDICTION MODEL ACCOUNTING FOR THE FMC WILL BE ASSESSED IN COLLABORATION WITH THE CENTER FOR EXCELLENCE FOR ADVANCED TECHNOLOGY AERIAL FIREFIGHTING USING OBSERVATIONS OF WILDLAND FIRES OVER COLORADO.
$924,043University Corporation For Atmospheric Research · · FY2020 · National Aeronautics and Space Administration
Discovery of Chemical Probes and Therapeutic Leads, Phase II
$924,001Joseph M Fox · University Of Delaware · P20 · FY2024 · GM
Exosome-based microRNA biomarkers for Non-invasive and Early Detection of Pancreatic Cancer
$923,881Ajay Goel · Beckman Research Institute/City Of Hope · U01 · FY2023 · CA
Center for Multi- and Trans-ethnic Mapping of Mendelian and Complex Diseases
$923,476Carlos D. Bustamante · Stanford University · U01 · FY2017 · HG
GenePattern and GenePattern Notebook: Integrative 'Omic Analysis for Cancer Research
$923,435Jill P. Mesirov · University Of California, San Diego · U24 · FY2021 · CA
Improving drug design to eliminate side effects: From computational to animal models
$923,348C. Denise Okafor · Pennsylvania State University, The · DP2 · FY2025 · GM