| Título |
Skin Cancer Diagnosis Enhancement Through NLP and DNN-Based Binary Classification |
| Tipo |
Libro |
| Sub-tipo |
Indefinido |
| Descripción |
Recent Developments and the New Directions of Research, Foundations, and Applications |
| Resumen |
In present work, we enhance the diagnosis of skin-cancer by applying Natural Language processing and Machine Learning techniques to a specific classification problem. Our experimentation with different architectures yielded noteworthy results over a specific corpora of medical notes. Using a BoW/TF-IDF representation of the corpus and a 1-dimensional Convolutional Neural Network(CNN1D) architecture, we achieved an F1-measure of 0.95, which is better than state of the art. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG. |
| Observaciones |
DOI 10.1007/978-3-031-23476-7_12
Studies in Fuzziness and Soft Computing, v. 423 |
| Lugar |
Cham |
| País |
Suiza |
| No. de páginas |
121-129 |
| Vol. / Cap. |
STUDFUZZ, v. 423 |
| Inicio |
2023-06-27 |
| Fin |
|
| ISBN/ISSN |
9783031234750 |
