Smart Health and Biomedical Research in the Era of Artificial Intelligence and Advanced Data Science (SCH)
Synopsis
This interagency program solicitation supports the development of transformative, high-risk/high-reward advances in computer and information science, engineering, mathematics, statistics, behavioral and/or cognitive research to address pressing questions in the biomedical and public health communities. Scientific and engineering innovations by interdisciplinary teams develop novel methods to collect, sense, connect, analyze, and interpret data from individuals, devices, and systems, enabling discovery and optimizing health. Solutions to these complex biomedical or public health challenges requires teams that are ready to address these issues, while advancing fundamental science and engineering.
Please watch the Smart and Connected Health presentation from ISMB 2022, which will give insight into how to prepare a successful application.
Read more about the National Science Foundation (NSF) Smart and Connected Health program.
Review full program guidelines and learn how to submit a proposal in the latest solicitation.
Read the NSF Solicitation 21-530
Read the NIH Notice NOT-OD-21-011
Upcoming Activities
Awardees
| Grant Number | Award IC | PI Name | PI Institution | Award Title |
|---|---|---|---|---|
|
1R01EY033847-01 |
NEI |
Truong Nguyen |
University of California San Diego |
SCH: Multimodal Retina Image Alignment and Applications |
|
1R01EY033861-01 |
NEI |
Tieming Liu |
Oklahoma State University |
SCH: Harnessing Tensor Information to Improve EHR Data Quality for Accurate Data-driven Screening of Diabetic Retinopathy with Routine Lab Results |
|
1R01CA270454-01 |
NCI |
Kwan-Liu Ma |
University of California, Davis |
SCH: Smart EHR Data Analytics to Enhance Cancer Care Multiteam Systems |
|
1R01HD108473-01 |
NICHD |
Yong Zhu |
North Carolina State University |
SCH: A personalized wearable rehabilitation sensing system for stroke survivors |
|
1R01HL163439-01 |
NHLBI |
Mounya Elhilali |
Johns Hopkins University |
SCH: Smart Auscultation for Pulmonary Diagnostics and Imaging |
|
1R01HL163515-01 |
NHLBI |
Thomas Stohmer |
University of California, Davis |
SCH: Heterogenous, dynamic synthetic data: From algorithms to clinical applications |
|
1R01EB032896-01 |
NIBIB |
Shandong Wu |
University of Pittsburgh |
SCH: Leverage clinical knowledge to augment deep learning analysis of breast images |
|
1R01NS126690-01 |
NINDS |
GQ Zhang |
The University of Texas Health Science Center at Houston (UTHealth Houston) |
SCH: Neurophysiological AI-Ready Data Resource |
|
1R01LM014026-01 |
NLM |
Cyrus Shahabi |
University of Southern California |
SCH: Wearables for Health and Disease Knowledge (W4H) |
|
1R01LM014027-01 |
NLM |
Shigang Chen |
University of Florida |
SCH: Enabling Data Outsourcing and Sharing for AI-powered Parkinsons Research |
|
1R01DE031832-01 |
NIDCR |
Rong Wang |
Illinois Institute of Technology |
SCH: Multidimensional Microfluidic Salivary Sensor with Adversarial Knowledge Distillation for Point-of-Care Assessment of Periodontitis and Comorbidities |
|
1R01AG077003-01 |
NIA |
Xiaopeng Zhao |
The University of Tennessee, Knoxville |
SCH: Robotic Caregiver to Comprehend, Assist, Relieve, and Evaluate for Patients with Alzheimer’s Disease (Robotic CARE for AD) |
|
1R01AG077016-01 |
NIA |
Fenglong Ma |
The Pennsylvania State University |
SCH: AI-Enhanced Multimodal Sensor-on-a-chip for Alzheimers Disease Detection |
|
1R01AG077017-01 |
NIA |
Edison Thomaz |
The University of Texas at Austin |
SCH: Digital Biomarker and Analytics for Cognitive Impairment with Mobile and Wearable Sensing |
|
1R01AG077018-01 |
NIA |
Meltem Izzetoglu |
Villanova University |
SCH: Assessment of Cognitive Decline using Multimodal Neuroimaging with Embedded Artificial Intelligence |
|
1R01AR080826-01 |
NIAMS |
Hyunglae Lee |
Arizona State University |
SCH: Smart User-Effective Data-Enabled (SUEDE) Shoe for Ankle Injury Prevention |
|
1R01NR020362-01 |
NINR |
Arjun Athreya |
Mayo Clinic in Rochester, Minnesota |
SCH: Wearable Augmented Prediction of Burnout in Nurses: A Synergy of Engineering, Bioethics, Nursing |
Awards made prior to FY21 can be found in the NIH RePORTER.
This page last reviewed on September 21, 2022