Prediction of the potency of bioactive compounds generally relies on linear or nonlinear quantitative structure-activity relationship (QSAR) models. Nonlinear models are generated using machine learning methods. We introduce a novel approach for pote...
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)
Feb 17, 2023
BACKGROUND AND PURPOSE: Colorectal cancer has become the third most common cancer worldwide, accounting for approximately 10% of cancer patients. Early detection of the disease is important for the treatment of colorectal cancer patients. Histopathol...
Journal of computer-aided molecular design
Feb 17, 2023
Aqueous solubility is the most important physicochemical property for agrochemical and drug candidates and a prerequisite for uptake, distribution, transport, and finally the bioavailability in living species. We here present the first-ever direct ma...
IEEE transactions on bio-medical engineering
Feb 17, 2023
Transrectal ultrasound is commonly used for guiding prostate cancer biopsy, where 3D ultrasound volume reconstruction is often desired. Current methods for 3D reconstruction from freehand ultrasound scans require external tracking devices to provide ...
BACKGROUND: Dental age (DA) estimation using two convolutional neural networks (CNNs), VGG16 and ResNet101, remains unexplored. In this study, we aimed to investigate the possibility of using artificial intelligence-based methods in an eastern Chines...
Computational intelligence and neuroscience
Feb 17, 2023
The convolution neural network (CNN) not only has high fault tolerance but also has high computing capacity. The image classification performance of CNN has an important relationship with its network depth. The network depth is deeper, and the fittin...
Measurement is at the heart of scientific research. As many-perhaps most-psychological constructs cannot be directly observed, there is a steady demand for reliable self-report scales to assess latent constructs. However, scale development is a tedio...
BACKGROUND: Delineation of Organs-at-Risks (OARs) is an important step in radiotherapy treatment planning. As manual delineation is time-consuming, labor-intensive and affected by inter- and intra-observer variability, a robust and efficient automati...
Modern computer vision algorithms are based on convolutional neural networks (CNNs), and both end-to-end learning and transfer learning modes have been used with CNN for image classification. Thus, automated brain tumor classification models have bee...
Resolving the structural variability of proteins is often key to understanding the structure-function relationship of those macromolecular machines. Single particle analysis using Cryogenic electron microscopy (CryoEM), combined with machine learning...
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