Identification of Micrometastasis in Cervical Lymph Nodes - A Machine Learning-Based Approach.

ABSTRACT:

Introduction and aim

Oral squamous cell carcinoma (OSCC) rates have been on the rise globally due to a lack of health care facilities, unaffordable treatment expenses and diagnosis at the advanced stages. Cervical lymph node metastasis is a critically important prognostic factor for OSCC patients. Micrometastatic deposits critically shape clinical staging and treatment choices. Microscopic examination for micrometastases is a slow, labour-intensive, and error-prone process. The use of machine learning on lymph node photomicrographs overcomes manual limitations and enables automated detection of metastatic tissue. This current study employed a convolutional neural network (CNN) algorithm to detect micrometastasis in lymph node sections.

Methods

Fifty lymph node archival tissu

SUBMITTER: Mondal K 

PROVIDER: S-EPMC12905756 | biostudies-literature | 2026 Feb

REPOSITORIES: biostudies-literature