This federal Project Grant award from the National Institute of Environmental Health Sciences (NIEHS) under the Medical Library Assistance (CFDA 93.879) program provides $249,000.00 to The Leland Stanford Junior University (Stanford University) to develop a Contrastive Feature Analysis (CFA) framework for reliable visualization of deep neural network feature spaces and designing high-performance deep neural networks for medical image analysis. The key objectives of this 3-year project, running from May 1, 2025 to April 30, 2028, are to: 1) develop an efficient CFA-based visualization technique for high-dimensional feature data, 2) apply the CFA framework to automatically refine deep neural network architectures for improved performance, and 3) demonstrate the potential of CFA in solving clinical problems. This research aims to address the lack of transparency and trustworthiness of deep neural networks, which has been a major barrier to their wider adoption in practical medical applications.
Mod # | Description | Reason For Modification | Federal Obligation (Click to sort descending) | Date (Click to sort ascending) |
|---|---|---|---|---|
| Not listed | $249.0k | 4/15/25 |