2023

V. I. Zakomirnyi, A. Moroz, R. Bhargava, and I. L. Rassakazov “Fluorescence enhancement via lossless all-dielectric spherical mesocavities” arXiv preprint arXiv:2301.10899. (2023)

K. Falahkheirkhah, S. Tiwari, K. Yeh, S. Gupta, L. H. Hernandez, M. R. McCarthy, R. E. Jimenez, J. C. Cheville, and R. Bhargava “Deepfake Histologic Images for Enhancing Digital Pathology” Laboratory Investigation (2023).
Paper | DOI: 10.1021/acs.analchem.2c04554

2022

P.H. Hsieh, Y. Phal, K. V. Prasanth, and R. Bhargava “Cell Phase Identification in a Three-Dimensional Engineered Tumor Model by Infrared Spectroscopic Imaging” Analytical Chemistry (2022).
Paper | DOI: 10.1016/j.labinv.2022.100006

S. Kenkel, M. Gryka, L. Chen, M. P. Confer, A. Rao, S. Robinson, K. V. Prasanth, and R. Bhargava “Chemical imaging of cellular ultrastructure by null-deflection infrared spectroscopic measurements” PNAS (2022).
Paper | DOI: 10.1073/pnas.2210516119

Y. Phal, L. Pfister, P. S. Carney, and R. Bhargava “Resolution Limit in Infrared Chemical Imaging” The Journal of Physical Chemistry C (2022).
Paper | DOI: 10.1021/acs.jpcc.2c00740

K. Falahkheirkhah, T. Guo, M. Hwang, P. Tamboli, C.G. Wood, J.A. Karam, K. Sircar, and R. Bhargava “A generative adversarial approach to facilitate archival-quality histopathologic diagnoses from frozen tissue sections” Laboratory Investigation (2022).
Paper | DOI: 10.1038/s41374-021-00718-y

S. Tiwari, K. Falahkheirkhah, G. Cheng, and R. Bhargava “Colon Cancer Grading Using Infrared Spectroscopic Imaging-Based Deep Learning” Applied Spectroscopy (2022).
Paper | DOI: 10.1177/00037028221076170

S. Mittal, J. Kim, and R. Bhargava “Statistical Considerations and Tools to Improve Histopathologic Protocols with Spectroscopic Imaging” Applied Spectroscopy (2022).
Paper | DOI: 10.1177/00037028211066327

R. J. Ho, Y. Phal, L. Lux, and R. Bhargava “Exploring the Study of miR-1301 Inhibiting the Proliferation and Migration of Squamous Cell Carcinoma YD-38 Cells through PI3K/AKT Pathway under Deep Learning Medical Images” Computational Intelligence and Neuroscience (2022).
Paper | DOI: 10.1155/2022/5865640

2021

K. Falahkheirkhah, K. Yeh, S. Mittal, L. Pfister, and R. Bhargava “Deep learning-based protocols to enhance infrared imaging systems” Chemometrics and Intelligent Laboratory Systems (2021). [Special Issue]
Paper | DOI: 10.1016.j.chemolab.2021.104390

E. Zimmerman*, S. Mukherjee*, K. Falahkheirkhah, M. Gryka, A. Kajdacsy-Balla, W. Hasan, G. Giraud, F. Tibayan, J. Raman, and R. Bhargava “Detection and Quantification of Myocardial Fibrosis Using Stain-Free Spectroscopic Imaging” Archives of Pathology & Laboratory Medicine (2021). [*Joint First Author]
Paper | DOI: 10.5858/arpa.2020-0635-OA

Y. Phal, K. Yeh, and R. Bhargava “EXPRESS: Design Considerations for Discrete Frequency Infrared Microscopy Systems” Applied Spectroscopy (2021).
Paper | DOI: 10.1177/00037028211013372

S. Mittal, T. Wrobel, M. Walsh, A. Kajdacsy-Balla, and R. Bhargava “Breast cancer histopathology using infrared spectroscopic imaging: The impact of instrumental configurations” Clinical Spectroscopy (2021).
Paper | DOI: 10.1016/j.clispe.2021.100006

K. Falahkheirkhah, and R. Bhargava “Enhancing hyperspectral imaging” Nature Machine Intelligence (2021).
Paper | DOI: 10.1038/s42256-021-00336-9

S. Tiwari, A. Kajdacsy-Balla, J. Whiteley, G. Cheng, S. Hewitt, and R. Bhargava “INFORM: INFrared-based ORganizational Measurements of tumor and its microenvironment to predict patient survival” Science Advances (2021).
Paper | DOI: 10.1126/sciadv.abb8292