The diagnosis of oral squamous cell carcinoma or oral leukoplakia and the presence or
absence of oral epithelial dysplasia is carried by pathologists. In recent years, deep learning …

The early detection of oral cancer is pivotal for improving patient survival rates. However, the
high cost of manual initial screenings poses a challenge, especially in resource-limited …

Oral squamous cell carcinoma (OSCC) is amongst the most common cancers, with more
than 377,000 new cases worldwide each year. OSCC prognosis remains poor, related to …

Convolutional neural network (CNN) has been widely utilized for benign-malignant
classification of pulmonary nodules in Computed Tomography images. For traditional CNN …

Oral epithelial dysplasia is a potentially malignant lesion that presents challenges for
diagnosis. The use of digital systems in histological analysis can aid specialists to obtain …

In this work, a computational scheme is proposed to identify the main combinations of
handcrafted descriptors and deep-learned features capable of classifying histological …

Oral epithelial dysplasia (OED) is a pre-cancerous histopathological diagnosis given to a
range of oral lesions. Architectural, cytological and histological features of OED can be …

Early diagnosis of potentially malignant disorders, such as oral epithelial dysplasia, is the
most reliable way to prevent oral cancer. Computational algorithms have been used as an …

The study of diseases via histological images with machine learning techniques has
provided important advances for diagnostic support systems. In this project, a study was …

In this work, an investigation based on ensemble learning is presented for the recognition of
patterns in histological tissues stained with Hematoxylin and Eosin, representative of breast …