Elisa Warner, PhD

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Austin, TX USA

Publications

See my Google Scholar Profile

  1. E. Warner, O. Siddiqui, M. Greenwald, T. Li, P. Gupta, J. Vempati, K. Srinivasan, A. Rao, H. Aravind, and N. Nallasamy. "Comparing IOL Refraction Prediction Accuracy in Cataract Surgery Patients across South Indian and Midwestern United States Populations. submitted.
  2. E. Warner, Advancing Clinical Outcome Prediction through Innovative Multimodal and Domain-Generalized AI that Accommodates Limited Data. PhD thesis, University of Michigan Ann Arbor, 2024.
  3. E. Warner, J. Lee, W. Hsu, T. Syeda-Mahmood, C. E. Kahn Jr, O. Gevaert, and A. Rao, “Multimodal machine learning in image-based and clinical biomedicine: Survey and prospects,” International Journal of Computer Vision, pp. 1–17, 2024.
  4. E. Warner, German Policy and Its Accommodation of the Turkish-German Minority: An Analysis of Integration and Multiculturalism in the 21st century. Undergraduate thesis, University of Michigan, 2015.
  5. E. Warner, N. Wang, J. Lee, and A. Rao, “Meaningful incorporation of artificial intelligence for personalized patient management during cancer: Quantitative imaging, risk assessment, and therapeutic outcomes,” in Artificial Intelligence in Medicine, pp. 339–359, Academic Press, 2020.
  6. E. Warner, N. Al-Turkestani, J. Bianchi, M. L. Gurgel, L. Cevidanes, and A. Rao, “Predicting osteoarthritis of the temporomandibular joint using random forest with privileged information,” in 2022 MICCAI Workshop on Multimodal Learning and Fusion Across Scales for Clinical Decision Support, vol. 13755, pp. 77–86, 2022.
  7. E. Warner, X. Li, G. Rao, J. Huse, J. Traylor, V. Ravikumar, V. Monga, and A. Rao, “Investigating useful features for overall survival prediction in patients with low-grade glioma using histology slides,” in 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), pp. 4938–4941, IEEE, 2022.
  8. J. Lee, E. Warner, S. Shaikhouni, M. Bitzer, M. Kretzler, D. Gipson, S. Pennathur, K. Bellovich, Z. Bhat, C. Gadegbeku, et al., “Clusa: Clustering-based spatial analysis framework through graph neural network for chronic kidney disease prediction using histopathology images,” medRxiv, pp. 2022–12, 2022.
  9. J. Zhu, E. Warner, and D. M. L. Neehar D. Parikh, “Glycoproteomic markers of hepatocellularcarcinoma-mass spectrometry based approaches,” Mass Spectrometry Reviews, vol. 9999, pp. 1–26, 2018.
  10. J. Lee, E. Warner, S. Shaikhouni, M. Bitzer, M. Kretzler, D. Gipson, S. Pennathur, K. Bellovich, Z. Bhat, C. Gadegbeku, S. Massengill, K. Perumal, J. Saha, Y. Yang, J. Luo, X. Zhang, L. Mariani, J. B. Hodgin, and A. Rao, “Clustering-based spatial analysis (CluSA) framework through graph neural network for chronic kidney disease prediction using histopathology images,” Scientific Reports, vol. 13, Aug. 2023.
  11. E. Sabeti, J. Drews, N. Reamaroon, E. Warner, M. W. Sjoding, J. Gryak, and K. Najarian, “Learning using partially available privileged information and label uncertainty: Application in detection of acute respiratory distress syndrome,” IEEE Journal of Biomedical and Health Informatics, pp. 1–1, 2020.
  12. M. B. Schultz, A. E. Kane, S. J. Mitchell, M. R. MacArthur, E. Warner, J. R. Mitchell, S. E. Howlett, M. S. Bonkowski, and D. A. Sinclair, “Age and life expectancy clocks based on machine learning analysis of mouse frailty,” Nature Communications, vol. 11, no. 1, pp. 1–12, 2020.
  13. J. Lee, E. Warner, S. Shaikhouni, M. Bitzer, M. Kretzler, D. Gipson, S. Pennathur, K. Bellovich, Z. Bhat, C. Gadegbeku, et al., “Unsupervised machine learning for identifying important visual features through bag-of-words using histopathology data from chronic kidney disease,” Scientific Reports, vol. 12, no. 1, p. 4832, 2022.
  14. S. Mohammed, T. Li, X. D. Chen, E. Warner, A. Shankar, M. F. Abalem, T. Jayasundera, T. W. Gardner, and A. Rao, “Density-based classification in diabetic retinopathy through thickness of retinal layers from optical coherence tomography.,” Scientific reports, vol. 10, no. 1, p. 15937, 2020.
  15. S. Mohammed, V. Ravikumar, E. Warner, S. Patel, S. Bakas, A. Rao, and R. Jain, “Quantifying t2-flair mismatch using geographically weighted regression and predicting molecular status in lower-grade gliomas,” American Journal of Neuroradiology, vol. 43, no. 1, pp. 33–39, 2022.
  16. W. Gong, A. Guerler, C. Zhang, E. Warner, C. Li, and Y. Zhang, “Integrating multimeric threading with high-throughput experiments for structural interactome of escherichia coli,” Journal of molecular biology, vol. 433, no. 10, p. 166944, 2021.
  17. J. Adomako, G. Q. Asare, A. Ofosu, B. E. Iott, T. Anthony, A. S. Momoh, E. V. Warner, J. P. Idrovo, R. Ward, and F. W. Anderson, “Community-based surveillance of maternal deaths in rural ghana,” Bulletin of the World Health Organization, vol. 94, no. 2, p. 86, 2016.
  18. L.-J. Du, C. Chu, E. Warner, Q.-Y. Wang, Y.-H. Hu, K.-J. Chai, J. Cao,L.-Q. Peng, Y.-B. Chen, J. Yang, et al., “Rapid microwave-assisted dispersive micro-solid phase extraction of mycotoxins in food using zirconia nanoparticles,” Journal of Chromatography A, vol. 1561, pp. 1–12, 2018.
  19. M. Wang, M. Fang, J. Zhu, H. Feng, E. Warner, C. Yi, J. Ji, X. Gu, and C. Gao, “Serum n-glycans outperform ca19-9 in diagnosis of extrahepatic cholangiocarcinoma,” Electrophoresis, vol. 38, no. 21, pp. 2749–2756, 2017. 2
  20. M. Wang, Y. Gao, H. Feng, E. Warner, M. An, J. Jia, S. Chen, M. Fang, J. Ji, X. Gu, et al., “A nomogram incorporating six easily obtained parameters to discriminate intrahepatic cholangiocarcinoma and hepatocellular carcinoma,” Cancer medicine, vol. 7, no. 3, pp. 646–654, 2018.
  21. J.-J. Xu, Q. Li, J. Cao, E. Warner, M. An, Z. Tan, S.-L. Wang, L.-Q. Peng, and X.-G. Liu, “Extraction and enrichment of natural pigments from solid samples using ionic liquids and chitosan nanoparticles,” Journal of Chromatography A, vol. 1463, pp. 32–41, 2016.
  22. D. Yan, J. R. L. Ruiz, M.-L. Hsieh, D. Jeong, M. Voroslakos, V. Lanzio, E. V. Warner, E. Ko, Y. Tian, P. R. Patel, et al., “Self-assembled origami neural probes for scalable, multifunctional, three-dimensional neural interface,” bioRxiv, pp. 2024–04, 2024.
  23. V. Prabhakar, E. Warner, and K. Liu, “Integrating cellular graph embeddings with tumor morphological features to predict in-silico spatial transcriptomics from h&e images,” bioRxiv, pp. 2023–10, 2023.