BACKGROUND: Biomarkers of angiogenesis and lymphangiogenesis have been explored in cancer prognostic models; however, their potential role in assessing local tumor invasiveness remains poorly understood.
BACKGROUND: Artificial intelligence (AI) has recently entered the medical field, but the level of readiness of medical students for it is not obvious. A tool with appropriate psychometric properties for use in different languages and for internationa...
BACKGROUND:  Given the high prevalence of hearing loss among truck drivers, using artificial neural networks (ANNs) to predict and detect contributing factors early can aid managers significantly.
Drought is a climate risk that affects access to safe water, crop development, ecological stability, and food production. Therefore, developing drought prediction methods can lead to better management of surface and groundwater resources. Similarly, ...
OBJECTIVE: The rapid adoption of Artificial Intelligence (AI) in health service delivery underscores the need for awareness, preparedness, and strategic utilization of AI's potential to optimize Primary Health Care (PHC) systems. This study aims to e...
BMC medical informatics and decision making
40098129
BACKGROUND: The HELLP syndrome represents three complications: hemolysis, elevated liver enzymes, and low platelet count. Since the causes and pathogenesis of HELLP syndrome are not yet fully known and well understood, distinguishing it from other pr...
BACKGROUND AND AIM: Colorectal cancer is among the most prevalent and deadliest cancers. Early prediction of metastasis in patients with colorectal cancer is crucial in preventing it from the advanced stages and enhancing the prognosis among these pa...
The South Khorasan Province in Iran is the main producer of seedless barberry, accounting for 98% of the country's production. This has led to significant economic growth in the region. However, the cultivation of barberry is threatened by the rust f...
BACKGROUND: Breast cancer (BC) is a major global health concern with rising incidence and mortality rates in many developing countries. Effective BC risk assessment models are crucial for prevention and early detection. While the Gail model, a tradit...
BACKGROUND: Acute myocardial infarction (AMI) remains a leading global cause of mortality. This study explores predictors of in-hospital mortality among AMI patients using advanced machine learning (ML) techniques.