Search Results for author:
Found 8 papers, 3 papers with code
Predicting Future States with Spatial Point Processes in Single Molecule Resolution Spatial Transcriptomics
In this paper, we introduce a pipeline based on Random Forest Regression to predict the future distribution of cells that are expressed by the Sog-D gene (active cells) in both the Anterior to posterior (AP) and the Dorsal to Ventral (DV) axis of the Drosophila in embryogenesis process.
Real-Time Diagnostic Integrity Meets Efficiency: A Novel Platform-Agnostic Architecture for Physiological Signal Compression
Head-based signals such as EEG, EMG, EOG, and ECG collected by wearable systems will play a pivotal role in clinical diagnosis, monitoring, and treatment of important brain disorder diseases.
Histopathology Slide Indexing and Search: Are We There Yet?
The search and retrieval of digital histopathology slides is an important task that has yet to be solved.
The State of Applying Artificial Intelligence to Tissue Imaging for Cancer Research and Early Detection
Artificial intelligence represents a new frontier in human medicine that could save more lives and reduce the costs, thereby increasing accessibility.
Multimodal Pathology Image Search Between H&E Slides and Multiplexed Immunofluorescent Images
We present an approach for multimodal pathology image search, using dynamic time warping (DTW) on Variational Autoencoder (VAE) latent space that is fed into a ranked choice voting scheme to retrieve multiplexed immunofluorescent imaging (mIF) that is most similar to a query H&E slide.
Generalizability of PRS313 for breast cancer risk amongst non-Europeans in a Los Angeles biobank
We found that the PRS313 achieved overlapping Areas under the ROC Curve (AUCs) in females of Lantix (AUC, 0. 68; 95 CI, 0. 65-0. 71) and European ancestry (AUC, 0. 70; 95 CI, 0. 69-0. 71) but lower AUCs for the AFR and EAA populations (AFR: AUC, 0. 61; 95 CI, 0. 56-0. 65; EAA: AUC, 0. 64; 95 CI, 0. 60-0. 680).
Clinically Relevant Latent Space Embedding of Cancer Histopathology Slides through Variational Autoencoder Based Image Compression
We generate and visualize embeddings from the compressed latent space and demonstrate how they are useful for clinical interpretation of data, and how in the future such latent embeddings can be used to accelerate search of clinical imaging data.
An Artificial Neural Network-Based Model Predictive Control for Three-phase Flying Capacitor Multi-Level Inverter
The case study herein is based on a four-level three-cell flying capacitor inverter.
