Journal of pharmacokinetics and pharmacodynamics
Mar 2, 2021
Quantitative systems pharmacology models are often highly complex and not amenable to further simulation and/or estimation analyses. Model-order reduction can be used to derive a mechanistically sound yet simpler model of the desired input-output rel...
Computer methods and programs in biomedicine
Mar 2, 2021
To diagnose Alzheimer's disease (AD), neuroimaging methods such as magnetic resonance imaging have been employed. Recent progress in computer vision with deep learning (DL) has further inspired research focused on machine learning algorithms. However...
International journal of computer assisted radiology and surgery
Mar 2, 2021
OBJECTIVES: It is with a great prospect to develop an auxiliary diagnosis system for dental periapical radiographs based on deep convolutional neural networks (CNNs), and the indications and performances should be investigated. The aim of this study ...
BACKGROUND: This study introduced machine learning approaches to predict newborn's body mass index (BMI) based on ultrasound measures and maternal/delivery information.
BACKGROUND: Deep learning contributes to uncovering molecular and cellular processes with highly performant algorithms. Convolutional neural networks have become the state-of-the-art tool to provide accurate and fast image data processing. However, p...
BACKGROUND: Estimating the depth of anaesthesia (DoA) is critical in modern anaesthetic practice. Multiple DoA monitors based on electroencephalograms (EEGs) have been widely used for DoA monitoring; however, these monitors may be inaccurate under ce...
The article summarizes various publications on the application of "learning algorithms" and "artificial neural networks" in psychiatry to describe a dystopian future scenario. The draft of a nosology based on molecular biology is opposed to the ecolo...
Microbes can metabolize more chemical compounds than any other group of organisms. As a result, their metabolism is of interest to investigators across biology. Despite the interest, information on metabolism of specific microbes is hard to access. I...
We present DeepMIB, a new software package that is capable of training convolutional neural networks for segmentation of multidimensional microscopy datasets on any workstation. We demonstrate its successful application for segmentation of 2D and 3D ...
Class imbalance poses a challenge for developing unbiased, accurate predictive models. In particular, in image segmentation neural networks may overfit to the foreground samples from small structures, which are often heavily under-represented in the ...
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