Artificial intelligence and high-resolution anoscopy: automatic identification of anal squamous cell carcinoma precursors using a convolutional neural network.
Miguel Mascarenhas SaraivaL SpindlerN FathallahH BeaussierC MammaM QuesnéeT RibeiroJ AfonsoM CarvalhoR MouraP AndradeH CardosoJ AdamJ FerreiraG MacedoV de ParadesPublished in: Techniques in coloproctology (2022)
The CNN architecture for application to HRA accurately detected precursors of squamous anal cancer. Further development and implementation of these tools in clinical practice may significantly modify the management of these patients.
Keyphrases
- convolutional neural network
- artificial intelligence
- deep learning
- squamous cell carcinoma
- machine learning
- end stage renal disease
- high grade
- high resolution
- clinical practice
- big data
- chronic kidney disease
- ejection fraction
- newly diagnosed
- healthcare
- primary care
- peritoneal dialysis
- papillary thyroid
- prognostic factors
- mass spectrometry
- lymph node metastasis
- quality improvement
- squamous cell
- radiation therapy
- young adults
- liquid chromatography