Author

Hongchang Gao

Temple UniversityORCID 0000-0002-0121-0953Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

Click to filter author papers

Signature Assays, Organisms & Methods

Click to filter · or open tag

Approach:deep learning· 1 Research Focus:differential expression· 1 Approach:diffusion model· 1 Organism:human· 1 Assay:imaging· 1 Approach:statistical model· 1 Research Focus:variant effect prediction· 1 Assay:whole-exome sequencing· 1

Frequent Co-Authors

Xinghua Mindy ShiiD· 2 shared Arif O. HarmanciiD· 1 shared Bin LiiD· 1 shared Bradley MaliniD· 1 shared Kai ZhangiD· 1 shared the Alzheimer’s Disease Neuroimaging Initiative· 1 shared Xiaoqian JiangiD· 1 shared Бин ЛиiD· 1 shared

Activity by Year

2023-2025 · peak 1/yr

Co-Author Collaboration Network

8 top collaborators · 22 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

2 shared papersBioinformatics

Xinghua Mindy ShiORCID

Mutual co-authors in cluster

Author profile →

2 papers

Recent·Most cited

BioinformaticsPLOS Digital HealthPeer-reviewedMay 30, 2025

Enhancing Fairness in Disease Prediction by Optimizing Multiple Domain Adversarial Networks

Bin Li, Xiaoqian Jiang, Kai Zhang…·the Alzheimer’s Disease Neuroimaging Initiative

This paper introduces a Multiple Domain Adversarial Neural Network (MDANN) to improve fairness in disease prediction by reducing biases in brain imaging data for Alzheimer's and Autism populations.

7 citationstop 4%

humanimaging

𝕏 PostBluesky

BioinformaticsbioRxivPreprintJan 17, 2023

FedDP: Secure Federated Learning for Disease Prediction with Imbalanced Genetic Data

Бин Ли, Hongchang Gao, Xinghua Mindy Shi

FedDP improves disease prediction from imbalanced genetic data by combining federated learning with differential privacy and a weighted minmax loss.

3 citations

whole-exome sequencingdiffusion model

𝕏 PostBluesky