Muhammad Khalid Khan Niazi, PhD
- Assistant Professor, General Internal Medicine

Muhammad Khalid Khan Niazi, PhD
Research Interests
- Image Interpretation, Computer-Assisted
- Digital Pathology
- Machine Learning
- Medical Image Analysis
- Positions
- Assistant Professor, General Internal Medicine
- Departments and Affiliations
- General Internal Medicine
- Center for Biomedical Informatics
Research
- CXCL1: A new diagnostic biomarker for human tuberculosis discovered using Diversity Outbred mice. Koyuncu D, Niazi MKK, Tavolara T, Abeijon C, Ginese ML, Liao Y, Mark C, Specht A, Gower AC, Restrepo BI, Gatti DM, Kramnik I, Gurcan M, Yener B, Beamer G. PLoS Pathog. 2021 Aug; 17(8):e1009773.
- Identification of difficult to intubate patients from frontal face images using an ensemble of deep learning models. Tavolara TE, Gurcan MN, Segal S, Niazi MKK. Comput Biol Med. 2021 Aug; 136:104737.
- Deep learning predicts gene expression as an intermediate data modality to identify susceptibility patterns in Mycobacterium tuberculosis infected Diversity Outbred mice. Tavolara TE, Niazi MKK, Gower AC, Ginese M, Beamer G, Gurcan MN. EBioMedicine. 2021 May; 67:103388.
- Wiley, Advanced Engineering Materials. Meryem Uzun-Per, Gregory J Gillispie, Thomas Erol Tavolara, James J Yoo, Anthony Atala, Metin Nafi Gurcan, Sang Jin Lee, Muhammad Khalid Khan Niazi. Automated Image Analysis Methodologies to Compute Bioink Printability. 2020 Dec; 2;
- Digital Otoscopy Videos Versus Composite Images: A Reader Study to Compare the Accuracy of ENT Physicians. Binol H, Niazi MKK, Essig G, Shah J, Mattingly JK, Harris MS, Elmaraghy C, Teknos T, Taj-Schaal N, Yu L, Gurcan MN, Moberly AC. Laryngoscope. 2021 05; 131(5):E1668-E1676.