Drug development and industrial pharmacy
Jun 11, 2015
This study for the first time demonstrates combined application of mixture experimental design and artificial neural networks (ANNs) in the solid dispersions (SDs) development. Ternary carbamazepine-Soluplus®-poloxamer 188 SDs were prepared by solven...
IEEE transactions on neural networks and learning systems
Apr 24, 2015
This paper addresses the problem of adaptive neural output-feedback control for a class of special nonlinear systems with the hysteretic output mechanism and the unmeasured states. A modified Bouc-Wen model is first employed to capture the output hys...
Journal of minimally invasive gynecology
Mar 10, 2015
Two types of laparoscopic or robotic-assisted vesicovaginal fistula (VVF) repairs, the traditional transvesical (O'Conor) and extravesical techniques, dominate the literature. The objectives of this study are to compare success rates between laparosc...
This work aimed to compare the predictive capacity of empirical models, based on the uniform design utilization combined to artificial neural networks with respect to classical factorial designs in bioprocess, using as example the rabies virus replic...
Controlled clinical trials are usually supported with an in-front data aggregation system, which supports the storage of relevant information according to the trial context within a highly structured environment. In contrast to the documentation of c...
OBJECTIVES: To examine the use of supervised machine learning to identify biases in evidence selection and determine if citation information can predict favorable conclusions in reviews about neuraminidase inhibitors.
BACKGROUND AND OBJECTIVE: The importance of data standards when integrating clinical research data has been recognized. The common data element (CDE) is a consensus-based data element for data harmonization and sharing between clinical researchers, i...
Giornale italiano di cardiologia (2006)
Aug 1, 2025
Integrating artificial intelligence (AI) into cardiovascular clinical trials is emerging as a key factor in streamlining patient selection, data collection, endpoint monitoring, and outcome analysis. On the one hand, machine learning and deep learnin...
BACKGROUND: Sepsis is a leading cause of mortality worldwide, characterized by a dysregulated host response to infection. Despite the development of multiple clinical practice guidelines (CPGs) to standardize sepsis management, substantial variabilit...
INTRODUCTION: Identifying difficult airways and avoiding unanticipated difficult airways through difficult airway assessment are crucial for patient safety prior to airway management. Therefore, accurately predicting difficult airways through airway ...
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