Background: The use of artificial intelligence (AI) in health care has grown exponentially with
the promise of facilitating biomedical research and enhancing diagnosis, treatment …

In the 21st century, the development of medical science has entered the era of big data, and
machine learning has become an essential tool for mining medical big data. The …

Background Ovarian cancer is the fifth leading cause of mortality among women in the
United States. Ovarian cancer is also known as forgotten cancer or silent disease. The …

Background Lung cancer is a malignant tumour, and early diagnosis has been shown to
improve the survival rate of lung cancer patients. In this study, we assessed the use of …

Aim: Method: This research presents a model combining machine learning (ML) techniques
and eXplainable artificial intelligence (XAI) to predict breast cancer (BC) metastasis and …

Background Fibromyalgia (FM) is a multifaceted disease. Along with the genetic,
environmental and neuro-hormonal factors, inflammation has been assumed to have role in …

Patients with parathyroid carcinoma (PC) are often diagnosed postoperatively, due to
incomplete resection during the initial surgery, resulting in poor outcomes. The aim of our …

Objective Hospitalized cancer patients are at high risk of venous thromboembolism (VTE).
However, no predictive model has been specifically developed for this population. Machine …

Objective Distant metastasis of thyroid cancer often indicates poor prognosis, and it is
important to identify patients who have developed distant metastasis or are at high risk as …

Introduction Memory-related diseases (MDs) pose a significant healthcare challenge
globally, and early detection is essential for effective intervention. This study investigates the …