This study proposes a novel approach to predict the efficacy of bevacizumab (BEV) in treating peritumoral edema in metastatic brain tumor patients by integrating advanced machine learning (ML) techniques with comprehensive imaging and clinical data. ...
With the extensive application of artificial intelligence technology in the tourism industry, robot-assisted tourism has become a vital strategy for enhancing tourist experiences and promoting sustainable tourism practices. This study aims to explore...
This study was conducted aiming to investigate impacts of experimentally induced endometritis on the vascular perfusion and echogenicity of the endometrium in dairy cows. Following estrus synchronization and applying cytological and bacteriological e...
Early identification of patients who require onward referral to social care can prevent delays to discharge from hospital. We introduce an explainable machine learning (ML) model to identify potential social care needs at the first point of admission...
This study aimed to demonstrate whether plasma galectin-3 could predict the development of postoperative delirium (POD) in patients with acute aortic dissection (AAD). Prospective, observational study. Cardiac surgery intensive care unit. Consecutive...
Heavy metal exposure is acknowledged as a risk factor for poor health. However, the effect of heavy metal exposure on the prevalence of gallstones is still unknown. Therefore, we investigated the relationship between heavy metal concentrations and th...
This study proposes a method for measuring the height and weight of a neonate conveniently, safely, and accurately by applying a convolutional neural network to frequency-modulated continuous-wave (FMCW) radar sensor data. Fifteen neonates, with pare...
Rapidly increasing healthcare spending globally is significantly driven by high-need, high-cost (HNHC) patients, who account for the top 5% of annual healthcare costs but over half of total expenditures. The programs targeting existing HNHC patients ...
An accurate and reliable functional prognosis is vital to stroke patients addressing rehabilitation, to their families, and healthcare providers. This study aimed at developing and validating externally patient-wise prognostic models of the global fu...
Globally, mental disorders are a significant burden, particularly in low- and middle-income countries, with high prevalence in Rwanda, especially among survivors of the 1994 genocide against Tutsi. Machine learning offers promise in predicting mental...