Enhancing Thyroid Pathology With Artificial Intelligence: Automated Data Extraction From Electronic Health Reports Using RUBY.

Purpose: Thyroid nodules are common in the general population, and assessing their malignancy risk is the initial step in care. Surgical exploration remains the sole definitive option for indeterminate nodules. Extensive database access is crucial for improving this initial assessment.

Prognostic impact of intra tumoral HPV-16 viral load in oropharyngeal squamous cell carcinomas.

Objectives: The incidence of HPV-induced oropharyngeal squamous cell carcinoma (OSCC) is constantly increasing. Although HPV-related OSCC carry a better prognosis, the majority of patients with an HPV-positive OSCC have other prognostic factors such as tobacco smoking, making therapeutic de-escalating approaches less precise. In this context, our study aims to evaluate the prognostic impact of intra-tumoral HPV-16 viral load (VL) in OSCC.

Comparative Performance of Four Staging Classifications to Select «High-Risk» Head and Neck Cutaneous Squamous Cell Carcinomas.

Background: Many classifications exist to select patients with "high-risk" head and neck cutaneous squamous cell carcinoma (HNCSCC).

Objective: To compare the performance of the Brigham and Women's Hospital (BWH) classification with the performance of the American Joint Committee on Cancer 8th Edition (AJCC8), the Union for International Cancer Control 8th Edition (UICC8), and the National Comprehensive Cancer Network (NCCN) classifications.

Methods: In this single-center retrospective study, HNCSCC resected in a tertiary care center were classified as "low-risk" or "high-risk" tumors according to the four classifications.

Validation and Improvement of a Convolutional Neural Network to Predict the Involved Pathology in a Head and Neck Surgery Cohort.

The selection of patients for the constitution of a cohort is a major issue for clinical research (prospective studies and retrospective studies in real life). Our objective was to validate in real life conditions the use of a Deep Learning process based on a neural network, for the classification of patients according to the pathology involved in a head and neck surgery department. 24,434 Electronic Health Records (EHR) from the first visit between 2000 and 2020 were extracted.