Tehranifar, P., Lee Argov, E. J., Athilat, S., Liao, Y., Wei, Y., White, A. J., O’Brien, K. M., Sandler, D. P., & Terry, M. B. (2024). Longitudinal history of mammographic breast density and breast cancer risk by familial risk, menopausal status, and initial mammographic density level in a high risk cohort: a nested case–control study. Breast Cancer Research, 26(1). https://doi.org/10.1186/s13058-024-01917-3

Wang, H., Argenziano, M. G., Yoon, H., Boyett, D., Save, A., Petridis, P., Savage, W., Jackson, P., Hawkins-Daarud, A., Tran, N., Hu, L., Singleton, K. W., Paulson, L., Dalahmah, O. A., Bruce, J. N., Grinband, J., Swanson, K. R., Canoll, P., & Li, J. (2024). Biologically informed deep neural networks provide quantitative assessment of intratumoral heterogeneity in post treatment glioblastoma. Npj Digital Medicine, 7(1). https://doi.org/10.1038/s41746-024-01277-4

Tian, Y., Sharma, A., Mehta, S., Kaushal, S., Liebmann, J. M., Cioffi, G. A., & Thakoor, K. A. (2024). Automated Identification of Clinically Relevant Regions in Glaucoma OCT Reports Using Expert Eye Tracking Data and Deep Learning. Translational Vision Science & Technology, 13(10), 24. https://doi.org/10.1167/tvst.13.10.24

Saqi, A., Liu, Y., Politis, M. G., Salvatore, M., & Jambawalikar, S. (2024). Combined expert-in-the-loop—random forest multiclass segmentation U-net based artificial intelligence model: evaluation of non-small cell lung cancer in fibrotic and non-fibrotic microenvironments. Journal of Translational Medicine, 22(1). https://doi.org/10.1186/s12967-024-05394-2

Resch, D., Lo Gullo, R., Teuwen, J., Semturs, F., Hummel, J., Resch, A., & Pinker, K. (2024). AI-enhanced Mammography With Digital Breast Tomosynthesis for Breast Cancer Detection: Clinical Value and Comparison With Human Performance. Radiology: Imaging Cancer, 6(4). https://doi.org/10.1148/rycan.230149

Wang, L., Wang, H., D’Angelo, F., Curtin, L., Sereduk, C. P., Leon, G. D., Singleton, K. W., Urcuyo, J., Hawkins-Daarud, A., Jackson, P. R., Krishna, C., Zimmerman, R. S., Patra, D. P., Bendok, B. R., Smith, K. A., Nakaji, P., Donev, K., Baxter, L. C., Mrugała, M. M., … Li, J. (2024). Quantifying intra-tumoral genetic heterogeneity of glioblastoma toward precision medicine using MRI and a data-inclusive machine learning algorithm. PLOS ONE, 19(4), e0299267. https://doi.org/10.1371/journal.pone.0299267

Zogopoulos, G., Haimi, I., Sanoba, S. A., Everett, J. N., Wang, Y., Katona, B. W., Farrell, J. J., Grossberg, A. J., Paiella, S., Klute, K. A., Bi, Y., Wallace, M. B., Kwon, R. S., Stoffel, E. M., Wadlow, R. C., Sussman, D. A., Merchant, N. B., Permuth, J. B., Golan, T., … __. (2024). The Pancreatic Cancer Early Detection (PRECEDE) Study is a Global Effort to Drive Early Detection: Baseline Imaging Findings in High-Risk Individuals. Journal of the National Comprehensive Cancer Network, 22(3), 158–166. https://doi.org/10.6004/jnccn.2023.7097

Li, X., Liu, H., Song, X., Marboe, C. C., Brott, B. C., Litovsky, S. H., & Gan, Y. (2024). Structurally constrained and pathology-aware convolutional transformer generative adversarial network for virtual histology staining of human coronary optical coherence tomography images. Journal of Biomedical Optics, 29(03). https://doi.org/10.1117/1.jbo.29.3.036004

Rayn, K., Gupta, V., Mulinti, S., Clark, R., Magliari, A., Chaudhari, S., Garima, G., & Beriwal, S. (2024). Evaluation of a deep image-to-image network (DI2IN) auto-segmentation algorithm across a network of cancer centers. Journal of Cancer Research and Therapeutics, 20(3), 1020–1025. https://doi.org/10.4103/jcrt.jcrt_769_23

Beizavi, Z., Desperito, E., Capaccione, K. M., Patrizio, R., & Salvatore, M. M. (2023). Reporting breast density on chest computed tomography. Translational Breast Cancer Research, 4, 24–24. https://doi.org/10.21037/tbcr-23-36

Park, J., Artin, M. G., Lee, K. E., May, B. L., Park, M., Hur, C., & Tatonetti, N. P. (2023). Structured deep embedding model to generate composite clinical indices from electronic health records for early detection of pancreatic cancer. Patterns, 4(1), 100636. https://doi.org/10.1016/j.patter.2022.100636

Kehm, R. D., Walter, E. J., Pereira, A., White, M. L., Oskar, S., Michels, K. B., Shepherd, J. A., Lilge, L., & Terry, M. B. (2022). A comparison of various methods for measuring breast density and breast tissue composition in adolescent girls and women. Scientific Reports, 12(1). https://doi.org/10.1038/s41598-022-17800-0

Park, J., Artin, M. G., Lee, K. E., Pumpalova, Y. S., Ingram, M. A., May, B. L., Park, M., Hur, C., & Tatonetti, N. P. (2022). Deep learning on time series laboratory test results from electronic health records for early detection of pancreatic cancer. Journal of Biomedical Informatics, 131, 104095. https://doi.org/10.1016/j.jbi.2022.104095

Refaee, T., Salahuddin, Z., Widaatalla, Y., Primakov, S., Woodruff, H. C., Hustinx, R., Mottaghy, F. M., Ibrahim, A., & Lambin, P. (2022). CT Reconstruction Kernels and the Effect of Pre- and Post-Processing on the Reproducibility of Handcrafted Radiomic Features. Journal of Personalized Medicine, 12(4), 553. https://doi.org/10.3390/jpm12040553