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Maryam Pouryahya

Showing results (11-20 of 16) with videos related to

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Mabs|July 8, 2026
Predicting antibody self-association with sequence-structure fusion models: the central role of CSI-BLI in early developability screeningShafayat Ahmed, Federico Devalle, Lauren Leisen, et al.
Journal of Medical Imaging (Bellingham, Wash.)|May 6, 2021
Reproducibility of radiomic features using network analysis and its application in Wasserstein <i>k</i>-means clusteringJung Hun Oh, Aditya P Apte, Evangelia Katsoulakis, et al.
Cell Reports. Medicine|April 19, 2023
Integration of deep learning-based histopathology and transcriptomics reveals key genes associated with fibrogenesis in patients with advanced NASHJake Conway, Maryam Pouryahya, Yevgeniy Gindin, et al.
Mabs|April 1, 2025
Accelerating high-concentration monoclonal antibody development with large-scale viscosity data and ensemble deep learningLateefat A Kalejaye, Jia-Min Chu, I-En Wu, et al.
Medrxiv : the Preprint Server for Health Sciences|May 10, 2023
AI-based histologic scoring enables automated and reproducible assessment of enrollment criteria and endpoints in NASH clinical trialsJanani S Iyer, Harsha Pokkalla, Charles Biddle-Snead, et al.
Nature Medicine|August 7, 2024
AI-based automation of enrollment criteria and endpoint assessment in clinical trials in liver diseasesJanani S Iyer, Dinkar Juyal, Quang Le, et al.
Pageof 2

Showing results (11-20 of 16) with videos related to

Sort By:
Pageof 2
You have reached the last page of results.This site can display upto 16 results.
Mabs|July 8, 2026
Predicting antibody self-association with sequence-structure fusion models: the central role of CSI-BLI in early developability screeningShafayat Ahmed, Federico Devalle, Lauren Leisen, et al.
Journal of Medical Imaging (Bellingham, Wash.)|May 6, 2021
Reproducibility of radiomic features using network analysis and its application in Wasserstein <i>k</i>-means clusteringJung Hun Oh, Aditya P Apte, Evangelia Katsoulakis, et al.
Cell Reports. Medicine|April 19, 2023
Integration of deep learning-based histopathology and transcriptomics reveals key genes associated with fibrogenesis in patients with advanced NASHJake Conway, Maryam Pouryahya, Yevgeniy Gindin, et al.
Mabs|April 1, 2025
Accelerating high-concentration monoclonal antibody development with large-scale viscosity data and ensemble deep learningLateefat A Kalejaye, Jia-Min Chu, I-En Wu, et al.
Medrxiv : the Preprint Server for Health Sciences|May 10, 2023
AI-based histologic scoring enables automated and reproducible assessment of enrollment criteria and endpoints in NASH clinical trialsJanani S Iyer, Harsha Pokkalla, Charles Biddle-Snead, et al.
Nature Medicine|August 7, 2024
AI-based automation of enrollment criteria and endpoint assessment in clinical trials in liver diseasesJanani S Iyer, Dinkar Juyal, Quang Le, et al.
Pageof 2