Thambawita et al., 2020 - Google Patents
An extensive study on cross-dataset bias and evaluation metrics interpretation for machine learning applied to gastrointestinal tract abnormality classificationThambawita et al., 2020
View PDF- Document ID
- 12070303276364303858
- Author
- Thambawita V
- Jha D
- Hammer H
- Johansen H
- Johansen D
- Halvorsen P
- Riegler M
- Publication year
- Publication venue
- ACM Transactions on Computing for Healthcare
External Links
Snippet
Precise and efficient automated identification of gastrointestinal (GI) tract diseases can help doctors treat more patients and improve the rate of disease detection and identification. Currently, automatic analysis of diseases in the GI tract is a hot topic in both computer …
- 210000001035 Gastrointestinal Tract 0 title abstract description 49
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- G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
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- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/30—Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
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