One of the most prevalent cancers is oral squamous cell carcinoma, and preventing mortality
from this disease primarily depends on early detection. Clinicians will greatly benefit from …

Brain tumors pose a serious neurological threat to human life, necessitating improved
detection and classification methods. Deep transfer learning (TL), in particular in key tumor …

Transfer learning has recently been developed as a powerful technique for accurate
classification of medical images. It is predominantly used in deep learning models to …

Oral cancer poses a formidable global health threat, demanding urgent attention to combat
its devastating impact. Timely detection of oral squamous cell carcinoma (OSCC) is pivotal …

The study aims to identify histological classifiers from histopathological images of oral
squamous cell carcinoma using convolutional neural network (CNN) deep learning models …

The study presents a framework to analyze and detect meddling in real-time network data
and identify numerous meddling patterns that may be harmful to various communication …

Oral lesions are a prevalent manifestation of oral disease, and the timely identification of oral
lesions is imperative for effective intervention. Fortunately, deep learning algorithms have …

The present article aims to review and evaluate the practiced and classical techniques,
tools, models, and systems concerning automatic information extraction (IE) from published …

Oral squamous cell carcinoma (OSCC) is one of the deadliest and most common types of
cancer. The incidence of OSCC is increasing annually, which requires early diagnosis to …

Complex intracellular organizations are commonly represented by dividing the metabolic
process of cells into different organelles. Therefore, identifying sub-cellular organelle …