Evaluation framework for oncology foundation models (FMs)

a cutting-edge cell segmentation model specifically designed for single-molecule resolved spatial omics datasets. It addresses the challenge of accurately segmenting individual cells in complex imaging datasets, leveraging a unique approach based on graph neural networks (GNNs).

Using a Deep Learning CNN to detect acute lymphoblastic leukemia (ALL) from blood microscopy

VMAT modulation complexity index calculator based on https://github.com/victorgabr/ApertureComplexity

scMalignantFinder is a Python package specially designed for analyzing cancer single-cell RNA-seq datasets to distinguish malignant cells from their normal counterparts.

Point of care system for AMPATH clinics

Clinical oncology tumor board decision support system made by the Decider project.

Crossmapped phenotype ontologies for the oncology domain

Personalized Network-based Anti-Cancer Therapy Appointment

A python framework for creating image-guided cancer patient digital twins.

Clonal reconstruction from HTS data

🐝 | From Data to Prognosis: Embedding Multimodal Oncology Data for Precision Medicine

Code from my work as Radiation Physicist Assistant at Cookeville Regional Medical Center

Notes and procedures that I wrote as Radiation Physicist Assistant at Cookeville Regional Medical Center

A 3D lesion segmentation method on whole-body PET images including automated quality control.

A benchmark of histopathology Foundation Models on multi-stain Immunohistochemistry immune datasets AIM-FM workshop @ NeurIPS 24

A project focused on using single-cell RNA sequencing data (scRNA-seq) and pseudo time to improve colon cancer diagnosis and outcomes.

PD-1 Targeted Antibody Discovery Using AI Protein Diffusion

Read different files of TSO500 data analysis output and integrate the data.

🧠 | Multimodal Integration of Oncology Data System