15 citations · 22 across the 3 of their papers we have counts for
4 papers
An ensemble of machine learning and anti-learning methods for predicting tumour patient survival rates
Christopher Roadknight, Durga Suryanarayanan, Uwe Aickelin +2
This paper primarily addresses a dataset relating to cellular, chemical and physical conditions of patients gathered at the time they are operated upon to remove colorectal tumours…
Ensemble Learning of Colorectal Cancer Survival Rates
Chris Roadknight, Uwe Aickelin, John Scholefield +1
In this paper, we describe a dataset relating to cellular and physical conditions of patients who are operated upon to remove colorectal tumours. This data provides a unique insigh…
Biomarker Clustering of Colorectal Cancer Data to Complement Clinical Classification
Chris Roadknight, Uwe Aickelin, Alex Ladas +3
In this paper, we describe a dataset relating to cellular and physical conditions of patients who are operated upon to remove colorectal tumours. This data provides a unique insigh…
Supervised Learning and Anti-learning of Colorectal Cancer Classes and Survival Rates from Cellular Biology Parameters
Chris Roadknight, Uwe Aickelin, Guoping Qiu +2
In this paper, we describe a dataset relating to cellular and physical conditions of patients who are operated upon to remove colorectal tumours. This data provides a unique insigh…