57 citations · 72 across the 5 of their papers we have counts for
5 papers
A Multimodal Foundation Model for Longitudinal Patient Representation and Scalable Insight Generation in Oncology
Eugene Vorontsov, Yi Kan Wang, Alican Bozkurt +13
Precision oncology necessitates a longitudinal model of patient state that captures cancer evolution and treatment over time, integrating multimodal observations. We introduce the…
Virchow: A Million-Slide Digital Pathology Foundation Model
Eugene Vorontsov, Alican Bozkurt, Adam Casson +28
The use of artificial intelligence to enable precision medicine and decision support systems through the analysis of pathology images has the potential to revolutionize the diagnos…
Segmentation of Cellular Patterns in Confocal Images of Melanocytic Lesions in vivo via a Multiscale Encoder-Decoder Network (MED-Net)
Kivanc Kose, Alican Bozkurt, Christi Alessi-Fox +6
In-vivo optical microscopy is advancing into routine clinical practice for non-invasively guiding diagnosis and treatment of cancer and other diseases, and thus beginning to reduce…
A Multiresolution Convolutional Neural Network with Partial Label Training for Annotating Reflectance Confocal Microscopy Images of Skin
Alican Bozkurt, Kivanc Kose, Christi Alessi-Fox +4
We describe a new multiresolution "nested encoder-decoder" convolutional network architecture and use it to annotate morphological patterns in reflectance confocal microscopy (RCM)…
Delineation of Skin Strata in Reflectance Confocal Microscopy Images using Recurrent Convolutional Networks with Toeplitz Attention
Alican Bozkurt, Kivanc Kose, Jaume Coll-Font +4
Reflectance confocal microscopy (RCM) is an effective, non-invasive pre-screening tool for skin cancer diagnosis, but it requires extensive training and experience to assess accura…