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48,453 grants matching “machine learning”
A Statistical Physics Framework for Understanding the Role of Repeat RNA in Tumor Immunity
$649,506Benjamin Greenbaum · Sloan-Kettering Inst Can Research · U01 · FY2021 · CA
** AWARDS ISSUED PRIOR TO JANUARY 20, 2025, WERE FUNDED UNDER PREVIOUS ADMINISTRATIONS AND MAY NOT REFLECT THE PRIORITIES AND POLICIES OF THE CURRENT ADMINISTRATION.** BETTER DATA ANALYSIS MEANS BETTER FOOD SAFETY. IN RECENT YEARS, ARTIFICIAL INTELLIGENCE (AI)-POWERED SOLUTIONS ARE EMERGING IN AGRICULTURE AND FOOD SCIENCE DUE TO THEIR SUPERIOR PATTERN RECOGNITION AND PREDICTION CAPABILITY. INTEGRATION OF FOOD SCIENCE AND AI CAN HELP ADDRESS NEW CHALLENGES SUCH ASINCREASING VOLUME OF DATA ACQUIRED FROM MIXED SAMPLES AND COMPLEX FOOD MATRICES, WHICH POSES CHALLENGES TO DATA ANALYSIS USING TRADITIONAL METHODS.THE OVERALL GOAL IS TOINTEGRATE NOVEL MACHINE LEARNING (ML) METHODS, SUCH ASATTENTION-BASED DEEP NETWORKS,WITHSURFACE-ENHANCED RAMAN SPECTROSCOPY (SERS) PLATFORM FORMULTIPLEXDETECTION AND QUANTIFICATIONOF FOOD CONTAMINANTS WITH HIGH ACCURACY.SPECIFIC OBJECTIVES ARE TOSYNTHESIZE NANOSUBSTRATES AND ACQUIRE SERS SPECTRAL DATA OF DIFFERENT TYPES AND QUANTITIES OF PESTICIDES BY SERS MEASUREMENT;DEVELOPATTENTION-BASEDDEEP LEARNING PREDICTION METHODS FOR QUALITATIVE AND QUANTITATIVE ANALYSIS OF SINGLE FOOD CONTAMINANTS AND MULTIPLE/MIXED FOOD CONTAMINANTS; VALIDATE AND ASSESS SERS-ML TECHNIQUES FOR MULTIPLEX DETECTION OF CHEMICAL CONTAMINANTS IN FRESH PRODUCE; AND ESTABLISH PROTOCOLS/DATABASES FOR MEASURING FOOD CONTAMINANTS.THIS STUDY WILL BE THE FIRST SYSTEMATICINVESTIGATION OF PESTICIDES IN FRESH PRODUCE BY SERS COUPLED WITH MACHINE LEARNING ALGORITHMS, WHICH WILL BE MORE ACCURATE, SENSITIVE, AND RELIABLE THAN CURRENT METHODS. THE PROJECT WILL BROADEN THE APPLICATIONS OF DATA SCIENCE IN MAINTAINING THE SUSTAINABILITY OF U.S. AGRICULTURE AND FOOD SYSTEMS.
$649,483University Of Missouri System · · FY2023 · National Institute of Food and Agriculture
CAREER: Optimal High-Dimensional Estimators Using Sum-of-Squares Proof Systems
$649,475Tselil Schramm · Stanford University · · FY2022 · CSE
Cancer imaging phenomics software suite: application to brain and breast cancer
$649,474Christos Davatzikos · University Of Pennsylvania · U24 · FY2016 · CA
Confocal video-mosaicking microscopy to guide surgery of superficially spreading skin cancers
$649,426Milind Rajadhyaksha · Sloan-Kettering Inst Can Research · R01 · FY2022 · CA
Roles of novel cationic lipids in bacterial pathogenesis
$649,409Kelli Lea Palmer · University Of Texas Dallas · R01 · FY2024 · AI
Roles of novel cationic lipids in bacterial pathogenesis
$649,409Kelli Lea Palmer · University Of Texas Dallas · R01 · FY2025 · AI
Functional RNA elements in the human genome
$649,400Xiang-Dong Fu · University Of California, San Diego · R01 · FY2013 · HG
Creating an artificial intelligence therapy-to-data feedback loop for child developmental healthcare
$649,383Dennis Paul Wall · Stanford University · R01 · FY2021 · LM
Objective Integrated Multimodal Electrophysiological Index for the Quantification of Visceral Pain
$649,376Hugo Fernando Posada-Quintero · University Of Connecticut Storrs · R01 · FY2024 · DK
ENIGMA World Aging Center
$649,361Paul M Thompson · University Of Southern California · R01 · FY2023 · AG
Multi-level modeling to inform interventions for control of multidrug-resistant organisms within healthcare networks
$649,361Eili Ya'akov Klein · Center/ Disease Dynamics, Econom/Policy · U01 · FY2017 · CK
Targeting the Arrhythmogenic Sources of Human Atrial Fibrillation
$649,348Vadim V Fedorov · Ohio State University · R01 · FY2024 · HL
ENIGMA World Aging Center
$649,324Paul M Thompson · University Of Southern California · R01 · FY2024 · AG
Physician Assistance Technology in Image-guided Robotic Intervention of Prostate
$649,323Nobuhiko Hata · Brigham And Women'S Hospital · R01 · FY2024 · EB
Novel Integrative Approach for the Early Detection of Lung Cancer using Repeated Measures
$649,247Fabien Maldonado · Vanderbilt University Medical Center · R01 · FY2025 · CA
CAREER: Enabling High-throughput Creep Testing of Advanced Materials through in-situ Micromechanics and Mesoscale Modeling
$649,207Giacomo Po · University Of Miami · · FY2024 · ENG
** AWARDS ISSUED PRIOR TO JANUARY 20, 2025, WERE FUNDED UNDER PREVIOUS ADMINISTRATIONS AND MAY NOT REFLECT THE PRIORITIES AND POLICIES OF THE CURRENT ADMINISTRATION.** INFORMATION ON COTTON CROP DEVELOPMENT SUCH AS MATURITY, FRUIT RETENTION PATTERNS, AND PLANT ARCHITECTURE IS LIMITED TO NON-EXISTENT FOR MOST BREEDING AND OFFICIAL VARIETY TRIAL PROGRAMS IN THE U.S. DUE TO THE INFEASIBILITY OF TIME-CONSUMING MANUAL MEASUREMENTS. THE AUTOMATED PHENOTYPING TECHNOLOGIES AND RESULTING BIG DATA WOULD EMPOWER COTTON BREEDERS TO MAKE GREATER GENETIC GAINS AND SHORTEN SELECTION CYCLES. TO ADDRESS THE CHALLENGES FOR RESEARCHERS TO EFFECTIVELY MANAGE AND EFFICIENTLY PROCESS PHENOMICS DATA, THE OVERALL GOAL OF THIS PROJECT IS TO DEVELOP DATA SCIENCE TOOLS AND AI-BASED MODELS TO FACILITATE BREEDING COTTON GERMPLASM WITH IMPROVED IDEOTYPES. SPECIFIC OBJECTIVES OF THE PROPOSED PROJECT ARE TO: 1) MANAGE HETEROGENEOUS FIELD DATA BY DEVELOPING DATA CURATION, STORAGE, AND SHARING WORKFLOWS; 2) DEVELOP REAL-TIME VIDEO TRACKING AND 3D PLANT PART SEGMENTATION DEEP LEARNING MODELS TO MEASURE COTTON ORGAN-LEVEL HIGH RESOLUTION PHENOTYPES; AND 3) VALIDATE AND LEVERAGE PHENOMICS DATA FOR IDEOTYPE BREEDING TO MAXIMIZE COTTON YIELD. SIGNIFICANT IMPROVEMENT ON BREEDING EFFICIENCY WOULD MAKE U.S. COTTON INDUSTRY MORE SUSTAINABLE AND COMPETITIVE IN THE GLOBAL MARKET. THE METHODOLOGIES DEVELOPED IN THIS PROJECT WILL ALSO BENEFIT DATA DRIVEN DECISION SUPPORT SYSTEMS FOR OTHER CROPS AND MAKE THE AI-BASED TOOLS MORE BROADLY AVAILABLE TO CROP BREEDERS AND STAKEHOLDERS. THIS STANDARD RESEARCH PROJECT IS RELATED TO THE PROGRAM AREA DATA SCIENCE FOR FOOD AND AGRICULTURAL SYSTEMS (DSFAS) AND ADDRESSES THE AFRI PRIORITY AREA OF PLANT HEALTH AND PRODUCTION AND PLANT PRODUCTS. IN PARTICULAR, THIS PROJECT FOCUSES ON AI AND MACHINE LEARNING FOR MONITORING, ANALYTICS, AND AUTOMATION IN CROP DEVELOPMENT.
$649,189University Of Florida · · FY2023 · National Institute of Food and Agriculture
Multi-tissue high-throughput proteomic and genomic study in Parkinson's Disease
$649,168Bruno A. Benitez · Beth Israel Deaconess Medical Center · R01 · FY2022 · NS
** AWARDS ISSUED PRIOR TO JANUARY 20, 2025, WERE FUNDED UNDER PREVIOUS ADMINISTRATIONS AND MAY NOT REFLECT THE PRIORITIES AND POLICIES OF THE CURRENT ADMINISTRATION.** AQUIFER RESOURCES IN THE SOUTHERN HIGH PLAINS ARE DIMINISHING, AND RAINFED AGRICULTURE HAS BECOME A NECESSITY. OUR PROJECT CONCERNS HOW TO IMPROVE ON-THE-GROUND FARMING PRACTICES AND ASSOCIATED PROFITABILITY FOR RAINFED PRODUCTION IN THIS AREA. WE ADDRESS PROBLEMS COMMONLY SEEN IN RAINFED AGRICULTURE ACCORDING TO THREE RESEARCH OBJECTIVES--(1) QUANTIFYING SOIL HEALTH AND CROP YIELD USING THE, MEANING THAT WE FOCUS ON UNDERSTANDING AND IMPROVING PHYSICAL-CHEMICAL-BIOLOGICAL QUALITY OF SOILS AS A RESOURCE; (2) IMPROVING THE FIELD-SCALE UNDERSTANDING OF BIOCHAR MADE FROM COTTON GIN WASTE TO IMPROVE SOIL HEALTH ; AND (3) USING LARGE DATASETS TO EXPLAIN THE RELATIONSHIP BETWEEN RAIN-FED PRACTICES AND THEIR EFFECTS.THE ACTIVITIES WE WILL UNDERTAKE CONCERN RESEARCH CROP PLOTS THAT COMPARE ROTATION SCHEMES TO TAKE ADVANTAGE OF A SOIL HEALTH FOCUS AND STORING RAINFALL--CONVENTIONALLY TILLED COTTON, WHEAT-COTTON-FALLOW, AND RYE-SUMMER BLEND-COTTON. ADDITIONALLY, SOME PLOTS WILL HAVE VARYING APPLICATION OF COTTON GIN WASTE BIOCHAR. WE WILL MONITOR THESE PLOTS OVER THREE YEARS USING MULTISPECTRAL IMAGING AND SEMIANNUAL SOIL CORES TO PROVIDE MANY USEFUL CROP AND SOIL PROPERTIES THE EXPLAIN WHY DIFFERENT PRACTICES ARE OR ARE NOT EFFECTIVE IN RAINFED CROPPING. FINALLY, WE WILL USE MACHINE-LEARNING METHODS TO EXPLAIN AND PREDICT THE EFFECTS OF RAINFED CROP MANAGEMENT TECHNIQUES SPECIFICALLY IN THE AREAS OF YIELD PREDICTION, WEED DETECTION, AND DISEASE DETECTION USING DRONE IMAGERY. THE ULTIMATE AIM IS TO PROVIDE A DECISION-MAKING FRAMEWORK FOR PRODUCERS TO APPLY A RANGE OF RAINFED LINKED SOIL HEALTH PRACTICES SUITED TO THEIR GOALS.
$649,058Texas A&M University System,The · · FY2023 · National Institute of Food and Agriculture
Identifying adolescents at high risk of neurocognitive disorder: Development and validation of a composite risk index
$649,051Amara E Ezeamama · Michigan State University · R01 · FY2023 · NS
Precision Medicine Approach to Glucocortisteroids in Sepsis
$649,030Sachin Yende · University Of Pittsburgh At Pittsburgh · R01 · FY2022 · GM
Action for Health in Diabetes Brain Magnetic Resonance Imaging Ancillary Study
$649,018Mark Andrew Espeland · Wake Forest University Health Sciences · R01 · FY2013 · DK
Neurocomputational mechanisms of proactive social behavior deficits in autism spectrum disorder
$649,015Daniela Schiller · Icahn School Of Medicine At Mount Sinai · R01 · FY2024 · MH
Identification of Novel Agents to Treat PTSD using Clinical Data
$648,991Jaimie L. Gradus · Boston University Medical Campus · R01 · FY2020 · MH