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48,453 grants matching “machine learning”
Subthalamic and corticosubthalamic coding of speech production
$1,157,250Robert Mark Richardson · University Of Pittsburgh At Pittsburgh · U01 · FY2017 · NS
Analytics & Machine-learning for Maternal-health Interventions (AMMI): A Cross-CTSA Collaboration
$1,157,183Alison M Stuebe · Univ Of North Carolina Chapel Hill · U01 · FY2023 · TR
Identification of outcome-based sub-populations using deep phenotyping and precision functional mapping across ADHD and ASD
$1,157,073Damien A Fair · University Of Minnesota · R01 · FY2021 · MH
Multimodal machine learning for diagnosis and mechanistic phenotyping of inherited diseases
$1,156,956Kai Wang · Children'S Hosp Of Philadelphia · OT2 · FY2025 · OD
Immunoengineering
$1,156,567Kaitlyn Sadtler · National Institute Of Biomedical Imaging And Bioengineering · ZIA · FY2023 · EB
Predicting Pain Recovery: A Multimodality Machine-learning Approach using Harmonized Electronic Health Record Data
$1,156,554Catherine Daniela Chong · Mayo Clinic Arizona · OT2 · FY2025 · OD
Multi-Center Implementation and Validation of Efficient Magnetic Resonance Imaging and Analysis of Atherosclerotic Disease of the Cervical Carotid
$1,155,988Dennis L Parker · Utah State Higher Education System--University Of Utah · R01 · FY2025 · HL
Comprehensive Multivariable Deep Learning Models to Identify Predictors of Cognitive Change in PD
$1,155,000Charles Stanley Venuto · University Of Rochester · RF1 · FY2020 · NS
Disease, Disability and Death in an Aging Workforce
$1,154,772Mark Richard Cullen · Stanford University · R56 · FY2016 · AG
Technology to Identify and Assay Chemical Genomic Probes
$1,154,710Ronald Wayne Davis · Stanford University · R01 · FY2009 · HG
Improving Outcomes in Depression in Primary Care in a Low Resource Setting
$1,152,785Vikram H Patel · Harvard Medical School · R01 · FY2023 · MH
Multimodal MRI biomarkers of small vessel disease for older persons with and without dementia.
$1,152,217Julie A Schneider · Rush University Medical Center · UH3 · FY2019 · NS
Spinal Epidural Electrode Array To Facilitate Standing and Stepping After SCI
$1,152,001Reggie Edgerton · University Of California Los Angeles · U01 · FY2014 · EB
Enabling forelimb function with agonist drug and epidural stimulation in SCI
$1,151,858Reggie Edgerton · University Of California Los Angeles · U01 · FY2014 · EB
A data resource for high resolution neuropathological and omics analysis of Alzheimer's disease
$1,151,682Amy Bernard · Allen Institute · U19 · FY2021 · AG
THE NIA GENETICS OF ALZHEIMER'S DISEASE DATA STORAGE SITE
$1,151,283Li-San Wang · University Of Pennsylvania · U24 · FY2020 · AG
Coding Science Internships: Authentic Learning Experiences to Support Students' Science and Programming Practices and Broaden Participation in Computer Science
$1,151,234Eric J Greenwald · University Of California-Berkeley · · FY2017 · EDU
Identification of outcome-based sub-populations using deep phenotyping and precision functional mapping across ADHD and ASD
$1,150,757Damien A Fair · University Of Minnesota · R01 · FY2022 · MH
Identification of outcome-based sub-populations using deep phenotyping and precision functional mapping across ADHD and ASD
$1,150,208Damien A Fair · University Of Minnesota · R01 · FY2024 · MH
ENHANCE FULL-WAVEFORM INVERSION WITH MACHINE LEARNED LOW-FREQUENCY SIGNALS
$1,150,000Advanced Geophysical Technology Inc · · FY2019 · Department of Energy
** AWARDS ISSUED PRIOR TO JANUARY 20, 2025, WERE FUNDED UNDER PREVIOUS ADMINISTRATIONS AND MAY NOT REFLECT THE PRIORITIES AND POLICIES OF THE CURRENT ADMINISTRATION.** ENERGY AND PROTEIN FEEDING REPRESENT 65% OF MILK PRODUCTION COSTS. UNDERFEEDING NUTRIENTS RESULTS IN LOST REVENUE, AND OVERFEEDING CAUSES INCREASED COSTS AND ENVIRONMENTAL IMPACT. CURRENT SYSTEMS DO NOT ACCOMMODATE GENETIC DIVERSITY IN NUTRIENT REQUIREMENTS. DISCOVERING TRUE AMINO ACID REQUIREMENTS, AND FEEDING INDIVIDUALS TO MEET THOSE REQUIREMENTS SHOULD RESULT IN $0.22 TO $0.44/COW/DAY ADDITIONAL PROFIT AND 46 TO 92 G/COW/DAY REDUCTION IN NITROGEN EXCRETION.WE HAVE DEVELOPED A DATA COLLECTION AND FEEDING CONTROL SYSTEM THAT USES REAL-TIME DATA TO MONITOR ANIMAL PERFORMANCE, DISCOVER INDIVIDUAL ANIMAL AMINO ACID REQUIREMENTS, AND FORMULATE INDIVIDUL ANIMAL DIETS FED THROUGH ON-FARM AUTOMATED FEEDERS. WE PROPOSE TO COMPLETE DEVELOPMENT OF THE ANOMALY DETECTION SYSTEM, ASSESS ECONOMIC GAINS AND ENVIRONMENTAL IMPACT REDUTIONS WHEN USING THE SYSTEM ON 4 FARMS, DEVELOP EXTENSION PROGRAMMING BASED ON PROJECT RESULTS, AND CONDUCT EXTENSION PROGRAMMING ON NUTRIENT EFFICIENCY, DAIRY PROFIT, AND ENVIORNMENTAL IMPACTS. THE TEST DATA WILL BE MINED IN REAL-TIME TO IMPROVE OUR UNDERSTANDING OF THERMAL STRESS AND NUTRITION, ENVIRONMENT, AND MANAGEMENT FACTORS CONTRIBUTING TO HEALTH DISORDERS. EXTENSION PROGRAMMING FLOWING FROM THE PROJECT WILL BE USED TO IMPROVE PRODUCER AND NUTRITIONIST UNDERSTANDING AND COMPETENCY IN FEEDING AND ANIMAL MANAGEMENT.OVERALL, WE EXPECT THE LONG-TERM OUTCOMES OF THIS WORK TO BE BETTER MANAGEMENT PRACTICES INCLUDING MORE EFFICIENT FEED USE, A GROWING ACCEPTANCE OF USE OF TECHNOLOGY TO ACCOUNT FOR ON-FARM VARIATION, THE EMERGENCE OF ON-FARM APPLICATION OF MACHINE LEARNING, AND GREATER ECONOMIC AND MANAGEMENT INCENTIVES FOR DAIRY PRODUCERS. ULTIMATELY, THESE CHANGES WILL NOT ONLY IMPROVE THE BOTTOM LINE FOR DAIRIES BUT WILL ALSO IMPROVE THE SUSTAINABILITY OF US AGRICULTURE BY ALLOCATING FEWER LAND RESOURCES FOR MILK PRODUCTION. AS DATA ACCUMULATES OVER TIME, WE WILL BE ABLE TO DEVELOP BREEDING VALUES FOR EFFICIENCIES OF DM DIGESTIBILITY AND USE OF INDIVIDUAL METABOLIZED AMINO ACIDS FOR MILK AND BODY TISSUE. THE DATA WILL ALSO SUPPORT MAINTENANCE OF THE ENERGY EFFICIENCY PREDICTIONS. THIS WILL BE CRITICAL TO THE DEVELOPMENT OF A FEED EFFICIENCY SELECTION INDEX THAT INCORPORATES TRAITS INDICATIVE OF RUMEN FUNCTION AND EFFICIENCY BEYOND CURRENT GROWTH MEASURES.
$1,150,000Virginia Polytechnic Institute & State University · · FY2024 · National Institute of Food and Agriculture
COMBINATORIAL DISCOVERY OF HETEROGENEOUS CATALYSTS UTILIZING EMISSION SPECTROSCOPY AND ADVANCED MACHINE LEARNING
$1,150,000Accustrata Inc · · FY2018 · Department of Energy
Statistical and Computational Foundations of Deep Generative Models
$1,150,000Eric Vanden-Eijnden · New York University · · FY2021 · MPS
SHF: Medium: A Cloudless Universal Translator
$1,150,000David M Brooks · Harvard University · · FY2017 · CSE
SCH: Tackling Progressive Disease - Learning from Longitudinal Observational Clinical Data in the Presence of Noise and Confounding
$1,150,000Jenna Wiens · Regents Of The University Of Michigan - Ann Arbor · · FY2021 · CSE