Evaluation framework for oncology foundation models (FMs)
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Updated
Aug 8, 2024 - Python
Evaluation framework for oncology foundation models (FMs)
Crossmapped phenotype ontologies for the oncology domain
PD-1 Targeted Antibody Discovery Using AI Protein Diffusion
Clinical oncology tumor board decision support system made by the Decider project.
Point of care system for AMPATH clinics
Warlock is a snakemake workflow to spawn multiple demons (deme-based oncology models) as jobs running around on a cluster environment 😈😈
Research code for the investigation of the role of sample size in synthetic data generation
scMalignantFinder is a Python package specially designed for analyzing cancer single-cell RNA-seq datasets to distinguish malignant cells from their normal counterparts.
A 3D lesion segmentation method on whole-body PET images including automated quality control.
🧠 | Multimodal Integration of Oncology Data System
A systematic approach in using GEO2R for investigating gene expression differences between a low-metastatic group and the highly metastatic MDA-MB-231 (TNBC) human breast cancer cell lines.
A classifier prototype that predicts cancer cell line sex and genotype from gene-based sequencing read counts.
The study of how cancer cells gain stemness.
This work is an initial investigation into the predictive potential of a range of machine learning algorithms applied to baseline circulating biomarkers for the prognostic stratification of patients with advanced neuroendocrine tumours receiving 177Lu oxodotreotide therapy
Machine learning for non small cell lung cancer nodal staging from PETCT molecular imaging
Denoising Diffusion Medical Model (DDMM) on PyTorch for generating datasets of Acute Lymphoblastic Leukemia 🩺💜
NUS ZB4171: Building an image classification model to identify leukemia blast cells from normal healthy cells in microscopic images.
ESO speech dataset: an English-language speech corpus of the oncology domain for ASR training and benchmarking and MT benchmarking.
Zarządzanie magazynem odpadów radioaktywnych.
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