An isocratic reversed phase HPLC method for the simultaneous determination of doxorubicine (DOX) and celecoxib (CXB) out of a nanoparticulate fixed dose combination (NanoFDC) was developed and validated. Linearity of the results was demonstrated from...
BACKGROUND: To prevent persistent post-surgery pain, early identification of patients at high risk is a clinical need. Supervised machine-learning techniques were used to test how accurately the patients' performance in a preoperatively performed ton...
Cardiovascular imaging technologies continue to increase in their capacity to capture and store large quantities of data. Modern computational methods, developed in the field of machine learning, offer new approaches to leveraging the growing volume ...
A capillary zone electrophoresis (CZE) method for the quantitation of captopril (CPT) using UV detection was developed. Influence of electrolyte concentration and system variables on electrophoretic separation was evaluated and a central composite de...
Characterizing the binding behaviors of RNA-binding proteins (RBPs) is important for understanding their functional roles in gene expression regulation. However, current high-throughput experimental methods for identifying RBP targets, such as CLIP-s...
American journal of respiratory and critical care medicine
Aug 15, 2017
RATIONALE: Difficulty of asthma ascertainment and its associated methodologic heterogeneity have created significant barriers to asthma care and research.
Toxicity evaluation is an extremely important process during drug development. It is usually initiated by experiments on animals, which is time-consuming and costly. To speed up such a process, a quantitative structure-activity relationship (QSAR) st...
Technology and health care : official journal of the European Society for Engineering and Medicine
Jul 20, 2017
This paper presents a pattern recognition model using multiple features and the kernel extreme learning machine (ELM), improving the accuracy of automatic epilepsy diagnosis. After simple preprocessing, temporal- and wavelet-based features are extrac...
Current machine learning techniques provide the opportunity to develop noninvasive and automated glioma grading tools, by utilizing quantitative parameters derived from multi-modal magnetic resonance imaging (MRI) data. However, the efficacies of dif...
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