OBJECTIVES: This study aimed to develop and validate an explainable machine learning (ML) model to predict 28-day all-cause mortality in immunocompromised patients admitted to the intensive care unit (ICU). Accurate and interpretable mortality predic...
OBJECTIVE: Pituitary adenomas (PAs), craniopharyngiomas (CRs), Rathke's cleft cysts (RCCs), and tuberculum sellar meningiomas (TSMs) are common sellar region lesions with similar imaging characteristics, making differential diagnosis challenging. Thi...
BACKGROUND: Lower limb exoskeleton rehabilitation robot is a new technology to improve the lower limb motor function of stroke patients. Recovery of motor function after stroke is closely related to neuroplasticity in the motor cortex and associated ...
Journal of orthopaedics and traumatology : official journal of the Italian Society of Orthopaedics and Traumatology
May 3, 2025
BACKGROUND: Advancements in diagnostic and therapeutic modalities for giant cell tumors of bone (GCTB) have introduced molecular and radiological tools that refine clinical decision-making. H3.3 G34W immunohistochemical staining has become a routine ...
Chronic diseases are a critical focus in the management of elderly health. Early disease prediction plays a vital role in achieving disease prevention and reducing the associated burden on individuals and healthcare systems. Traditionally, separate m...
Post-hepatectomy liver failure (PHLF) is a severe complication following liver surgery. We aimed to develop a novel, interpretable machine learning (ML) model to predict PHLF. We enrolled 312 hepatocellular carcinoma (HCC) patients who underwent hepa...
INTRODUCTION: High-dose methotrexate is a typical chemotherapy that is widely used in the treatment of osteosarcoma. However, the unique dose-response relationship of methotrexate makes its treatment window relatively narrow, and its clinical use is ...
Proceedings of the National Academy of Sciences of the United States of America
May 2, 2025
Despite its importance to society and many decades of research, key questions about the social and psychological processes of political persuasion remain unanswered, often due to data limitations. We propose that AI tools, specifically generative lar...
BACKGROUND: Classification of the etiologies of pleural effusion is a critical challenge in clinical practice. Traditional diagnostic methods rely on a simple cut-off method based on the laboratory tests. However, machine learning (ML) offers a novel...
INTRODUCTION: Pneumonia is the leading cause of child morbidity and mortality and accounts for 5.6 million under-five child deaths. Pneumonia has a significant impact on the quality of life, the country's economy, and the survival of children. Theref...