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48,453 grants matching “machine learning”
1/2 Neurodevelopmental and clinical trajectories of youth at risk for bipolar I disorder
$811,720Stephen M Strakowski · University Of Texas At Austin · R01 · FY2023 · MH
A Deep Learning Model to Improve Pathologist Interpretation of Donor Kidney Biopsies
$811,695Joseph P Gaut · Newventureiq, Llc · R42 · FY2020 · DK
Big Data Digital Outreach and Epidemiology Methods for HIV Care among Communities of Color
$811,626Sean Young · University Of California-Irvine · R01 · FY2022 · MD
DORMIR: Determinants, Outcomes, Responses and Markers of Insufficient sleep in Rural-Urban settings
$811,585Azizi Seixas · University Of Miami School Of Medicine · R01 · FY2022 · HL
Altered metabolism and machine learning for pancreatic cancer early detection
$811,576Brian Matthew Wolpin · Dana-Farber Cancer Inst · U01 · FY2023 · CA
Data-driven subtyping in major depressive disorder
$811,567Roy H Perlis · Massachusetts General Hospital · R01 · FY2024 · MH
Mapping the superficial white matter connectome of the human brain using ultra high resolution multi-contrast diffusion MRI
$811,539Lauren Jean O'Donnell · Brigham And Women'S Hospital · R01 · FY2024 · MH
Mapping the superficial white matter connectome of the human brain using ultra high resolution multi-contrast diffusion MRI
$811,539Lauren Jean O'Donnell · Brigham And Women'S Hospital · R01 · FY2025 · MH
Mapping the superficial white matter connectome of the human brain using ultra high resolution multi-contrast diffusion MRI
$811,539Lauren Jean O'Donnell · Brigham And Women'S Hospital · R01 · FY2023 · MH
Digital Biomarkers for Alzheimerâs Disease
$811,479Ihab M Hajjar · Ut Southwestern Medical Center · R01 · FY2024 · AG
The structural & dynamic basis for the interdependence of drug resistance
$811,049Celia A. Schiffer · Univ Of Massachusetts Med Sch Worcester · P01 · FY2014 · GM
RI: Medium: Recognizing, Mitigating and Governing Bias in AI
$811,016Arvind Narayanan · Princeton University · · FY2018 · CSE
CURRENT UNDERSTANDING: ENHANCEMENTS OF>0.1 MEV/NUCLEON IONS NEAR 1 AU IN ASSOCIATION WITH THE PASSAGE OF AN INTERPLANETARY (IP) CORONAL MASS EJECTION (ICME) ARE OFTEN REFERRED TO AS ENERGETIC STORM PARTICLE (ESP) EVENTS. THE PRIMARY CANDIDATE OF PRODUCING THESE ENHANCEMENTS IS DIFFUSIVE SHOCK ACCELERATION (DSA). ESPS CAN PRODUCE SIGNIFICANT INCREASES IN THE NEAR-EARTH PARTICULATE RADIATION AND POSE SEVERE HAZARDS TO ASTRONAUTS AND HARDWARE IN SPACE. PHYSICAL PARAMETERS THOUGHT TO AFFECT ESP PRODUCTION INCLUDE IP SHOCK PROPERTIES (E.G. SPEED STRENGTH OBLIQUITY) AND UPSTREAM CONDITIONS AHEAD OF THE PROPAGATING SHOCK (E.G. TURBULENCE SEED POPULATIONS SW AND IMF CONDITIONS). WHILE SEVERAL OBSERVATIONAL STUDIES AND THEORIES HAVE ATTEMPTED TO LINK ESP PRODUCTION TO THESE DRIVERS RELIABLE PREDICTION OF ESP PROPERTIES (E.G. INTENSITIES SPECTRA ABUNDANCES) INCLUDING THEIR EVENT-TO-EVENT VARIABILITY HAS SO FAR PROVEN ELUSIVE INDICATING AN INCOMPLETE UNDERSTANDING OF HOW ICME-DRIVEN IP SHOCKS ACCELERATE ESPS. GOAL AND SCIENCE QUESTIONS: OUR OVERARCHING GOAL IS TO IDENTIFY THE DOMINANT UPSTREAM AND SHOCK PARAMETERS THAT INFLUENCE ESP PROPERTIES AND LEAD TO THEIR EVENT-TO-EVENT VARIABILITY THEREBY ADVANCING CURRENT UNDERSTANDING OF ICME-DRIVEN SHOCK PARTICLE ACCELERATION. WE WILL ALSO DETERMINE WHETHER THESE DRIVERS CAN BE USED TO PREDICT ESP PROPERTIES AT 1 AU. WE WILL ACHIEVE THIS GOAL BY ANSWERING THE FOLLOWING THREE SCIENCE QUESTIONS: Q1. WHAT IS THE RELATIONSHIP BETWEEN UPSTREAM CONDITIONS ESP PROPERTIES AND IP SHOCK PROPERTIES AT 1 AU? Q2. HOW DO UPSTREAM CONDITIONS AND IP SHOCK PROPERTIES AFFECT ESP PRODUCTION AND PROPERTIES? Q3. CAN UPSTREAM CONDITIONS AND IP SHOCK PROPERTIES BE USED TO PREDICT ESP PROPERTIES AT 1 AU? METHODOLOGY: WE USE ENERGETIC H-FE ION PLASMA AND MAGNETIC FIELD MEASUREMENTS FROM ACE WIND AND STEREO-A&B DURING SOLAR CYCLES 23 AND 24. USING SPECIFIC CRITERIA WE WILL IDENTIFY ALL SHOCKS AND ESP EVENTS MEASURED AT 1 AU. FOR EACH ESP AND WHEN AVAILABLE WE WILL DERIVE A MATRIX OF PARAMETERS DESCRIBING THE UPSTREAM CONDITIONS IP SHOCK AND ESP. STATISTICAL AND CORRELATION STUDIES WILL FOLLOW TO PINPOINT THE DOMINANT DRIVERS THAT INFLUENCE ESP PROPERTIES (Q1). ONCE THE UPSTREAM-SHOCK-ESP LINKAGE IS DETERMINED WE WILL UTILIZE THE PARTICLE ACCELERATION AND TRANSPORT IN THE INNER HELIOSPHERE (PATH) MODEL TO EXPLORE THE INFLUENCE OF THESE DOMINANT DRIVERS ON ESP PROPERTIES. PATH MODEL INPUTS CONSTRAINED BY OBSERVATIONS WILL BE VARIED SYSTEMATICALLY TO ISOLATE THE INFLUENCE OF EACH POTENTIAL DRIVER ON ESP INTENSITIES SPECTRA AND ABUNDANCES (Q2). USING THE PARAMETER MATRIX DERIVED IN Q1 WE WILL UTILIZE MACHINE LEARNING ALGORITHMS TO DETERMINE IF AND HOW UPSTREAM AND SHOCK PARAMETERS CAN BE USED TO PREDICT ESP PROPERTIES (Q3). THE RELATIONSHIPS UNCOVERED IN THESE ANALYSES ARE EXPECTED TO LEAD TO A MORE COMPLETE UNDERSTANDING OF ICME-DRIVEN PARTICLE ACCELERATION AT 1 AU. RELEVANCE TO NASA AND LWS: OUR PROJECT RESPONDS DIRECTLY TO THE SECOND FOCUSED SCIENCE TOPIC (FST) AND TO TWO LWS PROGRAM SCIENCE GOALS AS INDICATED IN THE SPECIAL FST CONTRIBUTIONS ELSEWHERE IN THIS PROPOSAL. RESULTS ARE ALSO RELEVANT TO TWO SCIENCE GOALS OF THE 2012 SOLAR AND SPACE PHYSICS DECADAL SURVEY AND TO A KEY STRATEGIC GOAL OF NASAS HELIOPHYSICS DIVISION I.E. UNDERSTAND THE SUN AND ITS INTERACTIONS WITH THE EARTH AND THE SOLAR SYSTEM INCLUDING SPACE WEATHER.
$810,868Southwest Research Institute · · FY2020 · National Aeronautics and Space Administration
Enhancing the quality of CBT in community mental health through AI-generated fidelity feedback
$810,832David Charles Atkins · Lyssn.Io, Inc. · R42 · FY2022 · MH
The Structure of Olfactory Neural and Perceptual Spaces
$810,807Sandeep R Datta · New York University School Of Medicine · U19 · FY2023 · NS
Assisted Identification and Navigation of Early Mental Health Symptoms in Children
$810,761Robert B. Penfold · Kaiser Foundation Research Institute · R01 · FY2021 · MH
Prospective sudden cardiac death risk stratification using CMR and echocardiography machine learning in mitral valve prolapse
$810,751Francesca N Delling · University Of California, San Francisco · R01 · FY2020 · HL
M-ISIC: A Multimodal Open-Source International Skin Imaging Collaboration Informatics Platform for Automated Skin Cancer Detection
$810,739Veronica Miriam Rotemberg · Sloan-Kettering Inst Can Research · U24 · FY2023 · CA
UAS-CLEAR: A new nationally representative longitudinal study of caregiving experiences and well-being across the lifecourse
$810,685Kira S Birditt · University Of Michigan At Ann Arbor · R01 · FY2024 · AG
Cardiovascular MRI Characterization of the Arrhythmogenic Heart in Nonischemic Cardiomyopathy
$810,587Reza Nezafat · Beth Israel Deaconess Medical Center · R01 · FY2021 · HL
CAREER: Differentiating mechanisms of ecological divergence in sympatric microbial populations using an integrated population genomics approach
$810,512Peter Bergholz · North Dakota State University Fargo · · FY2015 · BIO
Investigating Resistance and Resilience Mechanisms in Alzheimerâs Disease
$810,339Prashanthi Vemuri · Mayo Clinic Rochester · R01 · FY2023 · AG
Natural Language Processing and Automated Speech Recognition to Identify Older Adults with Cognitive Impairment
$810,274Alex D. Federman · Icahn School Of Medicine At Mount Sinai · R01 · FY2022 · AG
Eliminating Tobacco-Related Disparities amount African American Smokers
$810,198David W Wetter · University Of Utah · R01 · FY2017 · MD
Directed Evolution of Novel AAVs and Regulatory Elements for Selective Microglial Gene Expression
$810,122David V Schaffer · University Of California Berkeley · R01 · FY2023 · NS