# A computer-aided diagnostic system to characterize CT focal liver lesions: design and optimization of a neural network classifier

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/a-computer-aided-diagnostic-system-to-characterize-ct-focal-liver-lesions-design/

## Facts

| Field | Value |
| --- | --- |
| Author Names | M. Gletsos,Stavroula Mougiakakou,George K. Matsopoulos,Konstantina S. Nikita,Alexandra Nikita,Alexis Kelekis |
| Citations | 250 |
| DOI | 10.1109/titb.2003.813793 |
| Fields | Computer Science,Health Professions,Medicine |
| Open Access | true |
| OA Status | green |
| OA URL | http://doi.org/10.1109/TITB.2003.813793 |
| OpenAlex ID | https://openalex.org/W2156260858 |
| PMID | 14518728 |
| Type | article |
| Year | 2003 |

## Paper authors

- [Stavroula Mougiakakou](https://scholariq.org/researchers/stavroula-mougiakakou/)

## Paper journal

- [IEEE Transactions on Information Technology in Biomedicine](https://scholariq.org/journals/ieee-transactions-on-information-technology-in-biomedicine/)

## Paper primary topic

- [Artificial Intelligence in Healthcare](https://scholariq.org/topics/artificial-intelligence-in-healthcare/)

## Paper topics

- [Artificial Intelligence in Healthcare](https://scholariq.org/topics/artificial-intelligence-in-healthcare/)
- [AI in cancer detection](https://scholariq.org/topics/ai-in-cancer-detection/)
- [Liver Disease Diagnosis and Treatment](https://scholariq.org/topics/liver-disease-diagnosis-and-treatment/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.