Early prediction of liver cancer using longitudinal MRI
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Updated
May 13, 2025 - Python
Early prediction of liver cancer using longitudinal MRI
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
Predicting Hepatocellular Carcinoma through Supervised Machine Learning
"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.
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.
Machine Learning pipeline for predicting 1-year survival of Hepatocellular Carcinoma patients. Includes Exploratory Data Analysis (EDA), preprocessing, supervised models (DT, KNN, RF, GB, MLP, LR, SVC, Stacking) and evaluation.
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
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