Macrovascular complications are leading causes of morbidity and mortality in patients with type 2 diabetes mellitus (T2DM), yet early diagnosis of cardiovascular disease (CVD) in this population remains clinically challenging. This study aims to deve...
Pancreatic cystic neoplasms (PCNs) are a complex group of lesions with a spectrum of malignancy. Accurate differentiation of PCN types is crucial for patient management, as misdiagnosis can result in unnecessary surgeries or treatment delays, affecti...
Predicting treatment response is an important problem in real-world applications, where the heterogeneity of the treatment response remains a significant challenge in practice. Unsupervised machine learning methods have been proposed to address this ...
PURPOSE: By using data obtained with digital inhalers, machine learning models have the potential to detect early signs of deterioration and predict impending exacerbations of chronic obstructive pulmonary disease (COPD) for individual patients. This...
BACKGROUND: Accurate mortality risk prediction is crucial for effective cardiovascular risk management. Recent advancements in artificial intelligence (AI) have demonstrated potential in this specific medical field. Qwen-2 and Llama-3 are high-perfor...
BACKGROUND: Coronary heart disease (CHD) is a major cause of morbidity and mortality worldwide. Identifying key risk factors is essential for effective risk assessment and prevention. A data-driven approach using machine learning (ML) offers advanced...
Colorectal liver metastasis (CRLM) is a primary factor contributing to poor prognosis and metastasis in colorectal cancer (CRC) patients. This study aims to develop and validate a machine learning (ML)-based risk prediction model using conventional c...
Journal of surgical orthopaedic advances
May 12, 2025
Autogenous iliac crest bone grating has been the gold standard. Recently, intramedullary bone graft harvest using a reamer-irrigator-aspirator (RIA) had been gaining more interest among orthopedic surgeons. Twenty-four RIA bone graft harvesting proce...
Journal of cancer research and clinical oncology
May 11, 2025
PURPOSE: This study aims to develop an effective machine learning (ML)-based predictive model for the recurrence of borderline ovarian tumor (BOT), and provide the guidelines of accurate clinical diagnosis and precise treatment for patients.
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