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

Point of care system for AMPATH clinics

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

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

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

Crossmapped phenotype ontologies for the oncology domain

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

Personalized Network-based Anti-Cancer Therapy Appointment

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

Clonal reconstruction from HTS data

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

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

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

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

PD-1 Targeted Antibody Discovery Using AI Protein Diffusion

🧠 | Multimodal Integration of Oncology Data System