In recent years, the volume of digitalized web-based information utilizing modern computer-
based technology for data storage, processing, and analysis has grown rapidly. Humans …

Non-communicable diseases, such as cardiovascular disease, cancer, chronic respiratory
diseases, and diabetes, are responsible for approximately 71% of all deaths worldwide …

Objectives Predicting stroke mortality is crucial for personalized care. This study aims to
design and evaluate a machine learning model to predict one-year mortality after a stroke …

The utilization of Artificial Intelligence (AI) and Machine Learning (ML) is paving the way for
significant strides in patient diagnosis, treatment, and prognostication in neurocritical care …

Introduction Stroke is a time-critical condition and one of the leading causes of mortality and
disability worldwide. To decrease mortality and improve patient outcome by improving …

The last decade has seen significant advances in the accumulation of medical data, the
computational techniques to analyze that data, and corresponding improvements in …

Background. Diffuse large B‐cell lymphoma (DLBCL) is a heterogeneous non‐Hodgkin's
lymphoma with great clinical challenge. Machine learning (ML) has attracted substantial …

Background Stroke is a leading cause of mortality and disability worldwide and its
occurrence is expected to increase in the future. Blood biomarkers have proven their …

Objectives Stepwise linear regression (SLR) is the most common approach to predicting
activities of daily living at discharge with the Functional Independence Measure (FIM) in …

Objective We previously identified the independent predictors of recurrent relapse in
neuromyelitis optica spectrum disorder (NMOSD) with anti-aquaporin-4 antibody (AQP4-ab) …