BACKGROUND & OBJECTIVE: This study aimed to identify key immune-related biomarkers of benign schwannoma through machine learning-assisted transcriptomic and single-cell analyses, and to construct a predictive model for disease evaluation.
Environmental pollution by miniaturized plastics such as micro- and nanoplastics continues to escalate, posing serious risks to ecosystems and human health. Therefore, there is an urgent need to detect or identify the plastics. Although the technique...
The Maillard reaction generates hazardous processing contaminants, including acrylamide (AA) and Nε-(carboxymethyl)lysine (CML), necessitating effective inhibitors. Here we use machine learning approaches to predict how catechin treatment reduces sim...
Suicide prevention is currently a global public health priority, since suicide has been a prevalent cause of death or potential loss of life. Multiple factors contribute to suicide risk, such as depression and a history of attempted suicide among oth...
This study aims to develop a robust and accurate model to forecast 30-day readmissions for patients with diabetes by leveraging machine learning techniques. Diabetes, being a chronic condition with complex care needs, often leads to frequent hospital...
BACKGROUND AND OBJECTIVE: The COVID-19 pandemic plays a significant roles in the global health, highlighting the imperative for effective management of post-recovery symptoms. Within this context, Ground Glass Opacity (GGO) in lung computed tomograph...
Gastric cancer (GC) ranks as the fifth most commonly diagnosed malignancy and the fourth leading cause of cancer-related mortality worldwide. The integration of machine learning in the analysis of GC metabolomics data for biomarker identification rem...
Applying machine learning algorithms to physical signals is always challenging since undesirable events can occur when signals are acquired outside a controlled environment. Among several applications, movement recognition through sEMG signals is esp...
INTRODUCTION: Increased LDL cholesterol is one of the main risk factors for cardiovascular diseases; therefore, adequate therapy reduces the risk of developing cardiovascular disease. Artificial intelligence (AI) is a tool that can significantly help...
This study aims to optimize ibuprofen-based Drug Delivery Systems (DDSs) to address their short half-life and enhance controlled release. Advanced machine learning techniques, including Artificial Neural Networks, Random Forest, and CatBoost, were em...
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