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.

Desarrollo de modelos de predicción para estratificar pacientes de Hepatocarcinoma basados en el análisis de transcriptomas no codificantes.

[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