Deciphering patterns in the structural and functional anatomy of genes can prove to be very helpful in understanding genetic biology and genomics. Also, the availability of the multiple omics data, along with the advent of machine learning techniques...
The successful development of the image denoising techniques for low-dose computed tomography (LDCT) was largely owing to the public-domain availability of spatially-aligned high- and low-dose CT image pairs. Even though low-dose CT scans are also hi...
The matching of cognitive load and working memory is the key for effective learning, and cognitive effort in the learning process has nervous responses which can be quantified in various physiological parameters. Therefore, it is meaningful to explor...
Structural disorder is widespread in eukaryotic proteins and is vital for their function in diverse biological processes. It is therefore highly desirable to be able to predict the degree of order and disorder from amino acid sequence. It is, however...
Cardiac magnetic resonance quantitative T1-mapping is increasingly used for advanced myocardial tissue characterisation. However, cardiac or respiratory motion can significantly affect the diagnostic utility of T1-maps, and thus motion artefact detec...
Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research
Sep 7, 2020
OBJECTIVES: Hospital readmission is a main cost driver for healthcare systems, but existing works often had poor or moderate predictive results. Although the available information differs in different studies, improving prediction is different from t...
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Sep 7, 2020
PURPOSE: To develop a deep learning-based metal artifact reduction (DL-MAR) method using unpaired data and to evaluate its dosimetric impact in head and neck intensity-modulated radiation therapy (IMRT) compared with the water density override method...
This paper reports on research to design an ensemble deep learning framework that integrates fine-tuned, three-stream hybrid deep neural network (i.e., Ensemble Deep Learning Model, EDLM), employing Convolutional Neural Network (CNN) to extract facia...
PURPOSE: To compare the performance of iterative direct and indirect parametric reconstruction methods with indirect deep learning-based reconstruction methods in estimating tracer-kinetic parameters from highly undersampled DCE-MR Imaging breast dat...
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