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An Extensive Study on Cross-Dataset Bias and Evaluation Metrics
  Interpretation for Machine Learning applied to Gastrointestinal Tract
  Abnormality Classification

An Extensive Study on Cross-Dataset Bias and Evaluation Metrics Interpretation for Machine Learning applied to Gastrointestinal Tract Abnormality Classification

8 May 2020
Vajira Thambawita
Debesh Jha
Hugo Lewi Hammer
H. Johansen
Dag Johansen
P. Halvorsen
Michael A. Riegler
ArXivPDFHTML

Papers citing "An Extensive Study on Cross-Dataset Bias and Evaluation Metrics Interpretation for Machine Learning applied to Gastrointestinal Tract Abnormality Classification"

2 / 2 papers shown
Title
A Closer Look at AUROC and AUPRC under Class Imbalance
A Closer Look at AUROC and AUPRC under Class Imbalance
Matthew B. A. McDermott
Lasse Hyldig Hansen
Haoran Zhang
Giovanni Angelotti
Jack Gallifant
39
30
0
11 Jan 2024
DivergentNets: Medical Image Segmentation by Network Ensemble
DivergentNets: Medical Image Segmentation by Network Ensemble
Vajira Thambawita
Steven A. Hicks
P. Halvorsen
Michael A. Riegler
16
23
0
01 Jul 2021
1