ResearcherThe Ohio State University Wexner Medical CenterActive in the last 2 years
Muhammad Khalid Khan Niazi
Matched on ORCID iD 0000-0002-1278-7512; OpenAlex author ID A5034159054, A5125560678, A5132867958. Sources: OpenAlex.
Their work
- Papers
- 6 (first author 2, last author 4)
- Trials
- 0
- Grants
- 0
- Labs led
- 1
- Collaborators
- 8
2026: 6 papers
Papers 6
- Gene-structured histology for deriving and predicting pancreatic cancer molecular subtypes Last author DOI 10.1038/s41392-026-03051-2↗
- Patient-specific integration of RNA expression, methylation-derived replication-timing proxies, and histomorphology for pancreatic cancer subtyping. First author DOI 10.1371/journal.pone.0358246↗
- Inferring Clinically Relevant Molecular Subtypes of Pancreatic Cancer from Routine Histopathology Using Deep Learning Last author DOI 10.21203/rs.3.rs-8545050/v1↗
- Inferring Clinically Relevant Molecular Subtypes of Pancreatic Cancer from Routine Histopathology Using Deep Learning Last author DOI 10.64898/2026.01.06.26343539↗
- Gene–Morphology Alignment via Graph-Constrained Latent Modeling for Molecular Subtype Prediction from Histopathology in Pancreatic Cancer Last author DOI 10.64898/2026.03.05.26347711↗
- Personalized Morphology, Replication Timing, and RNA based Gene Expression Networks for Basal-like and Classical subtyping genes in Pancreatic Adenocarcinoma First author DOI 10.64898/2026.03.12.711434↗
Closest collaborators
The 8 strongest of 8 by collab_strength@1: shared papers, trials and grants, recent and small-team work weighing most.
- Alejandro Leyva · 4 shared papers, 2026 · strength 2.26
- Paper Patient-specific integration of RNA expression, methylation-derived replication-timing proxies, and histomorphology for… DOI 10.1371/journal.pone.0358246↗
- Paper Personalized Morphology, Replication Timing, and RNA based Gene Expression Networks for Basal-like and Classical subtyp… DOI 10.64898/2026.03.12.711434↗
- Paper Gene-structured histology for deriving and predicting pancreatic cancer molecular subtypes DOI 10.1038/s41392-026-03051-2↗
- Abdul Akbar · 4 shared papers, 2026 · strength 1.53
- Paper Gene-structured histology for deriving and predicting pancreatic cancer molecular subtypes DOI 10.1038/s41392-026-03051-2↗
- Paper Gene–Morphology Alignment via Graph-Constrained Latent Modeling for Molecular Subtype Prediction from Histopathology in… DOI 10.64898/2026.03.05.26347711↗
- Paper Inferring Clinically Relevant Molecular Subtypes of Pancreatic Cancer from Routine Histopathology Using Deep Learning DOI 10.21203/rs.3.rs-8545050/v1↗
- Upender Manne Manne · 2 shared papers, 2026 · strength 0.53
- Paper Inferring Clinically Relevant Molecular Subtypes of Pancreatic Cancer from Routine Histopathology Using Deep Learning DOI 10.21203/rs.3.rs-8545050/v1↗
- Paper Inferring Clinically Relevant Molecular Subtypes of Pancreatic Cancer from Routine Histopathology Using Deep Learning DOI 10.64898/2026.01.06.26343539↗
- Ashwini Kumar Esnakula · 2 shared papers, 2026 · strength 0.53
- Paper Inferring Clinically Relevant Molecular Subtypes of Pancreatic Cancer from Routine Histopathology Using Deep Learning DOI 10.21203/rs.3.rs-8545050/v1↗
- Paper Inferring Clinically Relevant Molecular Subtypes of Pancreatic Cancer from Routine Histopathology Using Deep Learning DOI 10.64898/2026.01.06.26343539↗
- Ashish Manne · 2 shared papers, 2026 · strength 0.53
- Paper Inferring Clinically Relevant Molecular Subtypes of Pancreatic Cancer from Routine Histopathology Using Deep Learning DOI 10.21203/rs.3.rs-8545050/v1↗
- Paper Inferring Clinically Relevant Molecular Subtypes of Pancreatic Cancer from Routine Histopathology Using Deep Learning DOI 10.64898/2026.01.06.26343539↗
- Susan Tsai · 2 shared papers, 2026 · strength 0.53
- Paper Inferring Clinically Relevant Molecular Subtypes of Pancreatic Cancer from Routine Histopathology Using Deep Learning DOI 10.21203/rs.3.rs-8545050/v1↗
- Paper Inferring Clinically Relevant Molecular Subtypes of Pancreatic Cancer from Routine Histopathology Using Deep Learning DOI 10.64898/2026.01.06.26343539↗
- Anne M. Noonan · 2 shared papers, 2026 · strength 0.53
- Paper Inferring Clinically Relevant Molecular Subtypes of Pancreatic Cancer from Routine Histopathology Using Deep Learning DOI 10.21203/rs.3.rs-8545050/v1↗
- Paper Inferring Clinically Relevant Molecular Subtypes of Pancreatic Cancer from Routine Histopathology Using Deep Learning DOI 10.64898/2026.01.06.26343539↗
- Vaibhav Sahai · 2 shared papers, 2026 · strength 0.53
- Paper Inferring Clinically Relevant Molecular Subtypes of Pancreatic Cancer from Routine Histopathology Using Deep Learning DOI 10.21203/rs.3.rs-8545050/v1↗
- Paper Inferring Clinically Relevant Molecular Subtypes of Pancreatic Cancer from Routine Histopathology Using Deep Learning DOI 10.64898/2026.01.06.26343539↗
How to reach this person
A chain of introductions through people who have published, run trials or held grants together (warm_path@1: fewest links first, then the strongest). Built from public records only; no contact details are kept.