Updates to staging models are needed to reflect a greater understanding of tumor behavior
and clinical outcomes for well-differentiated thyroid carcinomas. We used a machine …

Background Several staging systems have been developed to predict the risk of mortality in
patients with differentiated thyroid cancer (DTC). However, none of them have been shown …

Context The risk stratification of patients with differentiated thyroid cancer (DTC) is crucial in
clinical decision making. The most widely accepted method to assess risk of …

Purpose The objective of this study was to train machine learning models for predicting the
likelihood of recurrence in patients diagnosed with well-differentiated thyroid cancer. While …

Background Thyroid cancer ranges from well-differentiated lesions with an excellent
prognosis to anaplastic carcinoma, which is almost uniformly fatal. Thus, methods to assess …

Background This study aimed to establish and validate an accurate prognostic model, based
on demographic and clinical parameters, for predicting the cancer-specific survival (CSS) of …

In recent times, researchers have noticed that chronic diseases have become more
common. In the Kingdom of Saudi Arabia, the number of patients with thyroid cancer (TC) …

The molecular mechanisms driving thyroid cancer (TC) development and progression are
poorly understood, but identifying molecular pathways and hub genes abnormally active in …

Background: Death is uncommon in thyroid cancer patients, and the factors important in
predicting survival remain inadequately studied. The objective of this study was to assess …

Utilizing historical clinical datasets to guide future treatment choices is beneficial for patients
and physicians. Machine learning and feature selection algorithms (namely, Fisher's …