Studies in history and philosophy of science
Mar 19, 2025
Our paper explores new potentials for productive dialogue between public engagement with science (PEWS) and radical embodied cognitive science (RECS). We establish a strong connection between the two fields by highlighting parallels between the views...
INTRODUCTION: The landscape of early drug discovery is rapidly evolving, fueled by significant advancements in artificial intelligence (AI) and machine learning (ML), which are transforming the way drugs are discovered. As traditional drug discovery ...
INTRODUCTION: Prostate cancer (PCa) is a leading cause of cancer-related deaths among men, and accurate diagnosis is critical for effective management. Multiparametric MRI (mpMRI) has become an essential tool in PCa diagnosis due to its superior spat...
Viral hepatitis remains a major global health issue, with chronic hepatitis B (HBV) and hepatitis C (HCV) causing approximately 1 million deaths annually, primarily due to liver cancer and cirrhosis. More than 1.5 million people contract HCV each yea...
Stroke is a leading cause of death and disability in developed countries. We validated an AI-based prediction model for incident stroke using sensors such as fundus cameras and ophthalmoscopes for retinal images, along with socio-demographic data and...
BACKGROUND: IgA nephropathy (IgAN) is a leading cause of renal failure, characterized by significant clinical and pathological heterogeneity. Accurate subtype classification remains challenging due to overlapping clinical manifestations and the multi...
BACKGROUND: Postoperative pulmonary infection (POI) is strongly associated with a poor prognosis and has a high incidence in elderly patients undergoing major surgery. Machine learning (ML) algorithms are increasingly being used in medicine, but the ...
BACKGROUND: World Health Organization (WHO) identified noncommunicable diseases as the foremost risk to public health globally and the cause of approximately 80% of premature deaths. However, Cardiovascular diseases account for most of these prematur...
BACKGROUND: To evaluate the predictive utility of machine learning and nomogram in predicting in-hospital mortality in patients with acute myocardial infarction complicated by cardiogenic shock (AMI-CS), and to visualize the model results in order to...
OBJECTIVE: The purpose of the current study is to explore the value of a nomogram that integrates clinical factors and MRI white matter hyperintensities (WMH) radiomics features in predicting the prognosis at 90 days for patients with acute ischemic ...
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