L. J. Vaickus

Uncovering Additional Predictors of Urothelial Carcinoma from Voided Urothelial Cell Clusters Through a Deep Learning Based Image Preprocessing Technique

This paper develops a deep learning-based preprocessing tool to analyze urothelial cell clusters in urine cytology, identifying key markers of atypia that could improve machine learning applications in bladder cancer detection.

Development of Biologically Interpretable Multimodal Deep Learning Model for Cancer Prognosis Prediction

This paper develops a multimodal deep learning model for cancer prognosis that integrates gene expression, DNA methylation, histopathological imaging, and clinical data, showing improved performance over unimodal approaches.

Improving the Virtual Trichrome Assessment through Bridge Category Models

This paper assesses Virtual Trichrome technologies using Bridge Category Models to account for bridge ratings in Fibrosis staging of NASH tissue.

Mixed Effects Machine Learning Models for Colon Cancer Metastasis Prediction using Spatially Localized Immuno-Oncology Markers

This study uses mixed-effects machine learning to predict colon cancer metastasis by analyzing spatially localized immuno-oncology markers in tumor tissue.

A Large-Scale Internal Validation Study of Unsupervised Virtual Trichrome Staining Technologies on Non-alcoholic Steatohepatitis Liver Biopsies

This study validates the use of GANs for virtual trichrome staining of NASH liver biopsies, showing high correlation with real stains and clinical outcomes.

PathFlow-MixMatch for Whole Slide Image Registration: An Investigation of a Segment-Based Scalable Image Registration Method

The paper introduces a segment-based image registration method for whole slide images, showing improved alignment accuracy compared to full image registration.

Preliminary Evaluation of the Utility of Deep Generative Histopathology Image Translation at a Mid-Sized NCI Cancer Center

The paper evaluates deep generative models for histopathology image translation in a cancer center, demonstrating applications in nuclear-to-cytoplasm ratio calculation, synthetic IHC staining, and stain conversion for liver fibrosis staging.