Predicting Hepatocellular Carcinoma through Supervised Machine Learning

Simultaneous Integration of Gene Expression and Nutrient Availability for Studying the Metabolism of Hepatocellular Carcinoma Cell Lines | Ewelina Węglarz-Tomczak, Thierry D.G.A. Mondeel, Diewertje G.E. Piebes, Hans V. Westerhoff | Biomolecules 2021

A classifier written in R which predicts whether a patient, diagnosed with "Hepatocellular Carcinoma", is likely to live or die within a year

Data analysis for HCC screening study.

Research project to track movement of Hepatoceullar Carcinoma cells.

[KTH/HT17] BB2491 - Analysis of Data from High-throughput Molecular Biology Experiments (BigData) | Diary: cf. wiki

"Identification of Biomarkers for Early-Stage Hepatocellular Carcinoma (HCC)" aims to address the critical global challenge of late-stage cancer diagnosis, which significantly lowers patient survival rates. It explores microarray gene expression datasets from GEO to identify potential early-stage biomarkers for improved patient outcomes.

Early prediction of liver cancer development using longitudinal MRI