Latest AI and machine learning research in cultural competence for healthcare professionals.
Identification of unknowns is a bottleneck for large-scale untargeted analyses like metabolomics or drug metabolite identification. Ion mobility-mass spectrometry (IM-MS) provides rapid two-dimensional separation of ions based on their mobility through a neutral buffer gas. The mobility of an ion is related to its collision cross section (CCS) with the buffer gas, a physical property that is deter...
BACKGROUND: Evidence from new health technologies is growing, along with demands for evidence to inform policy decisions, creating challenges in completing health technology assessments (HTAs)/systematic reviews (SRs) in a timely manner. Software can decrease the time and burden by automating the process, but evidence validating such software is limited. We tested the accuracy of RobotReviewer, a ...
The core element of machine learning is a flexible, universal function approximator that can be trained and fit into the data. One of the main challen...
Understanding the distribution of life's variety has driven naturalists and scientists for centuries, yet this has been constrained both by the availa...
To address substantial heterogeneity in patient response to treatment of chronic disorders and achieve the promise of precision medicine, individualiz...
Our purpose was to assess the performance of full-dose (FD) PET image synthesis in both image and sinogram space from low-dose (LD) PET images and sin...
The ActiGraph has a high ability to measure physical activity; however, it lacks an accurate posture classification to measure sedentary behavior. The...
Alignment-free methods, more time and memory efficient than alignment-based methods, have been widely used for comparing genome sequences or raw seque...
Image generation is a long-standing problem in the machine learning and computer vision areas. In order to generate images with high diversity, we pro...
As machines that act autonomously on behalf of others-e.g., robots-become integral to society, it is critical we understand the impact on human decisi...
Advances in neuroimaging, genomic, motion tracking, eye-tracking and many other technology-based data collection methods have led to a torrent of high...
With the increasing acquisition of large-scale neural recordings comes the challenge of inferring the computations they perform and understanding how ...
The black sheep effect (BSE) describes the evaluative upgrading of norm-compliant group members (ingroup bias), and evaluative downgrading of deviant ...
Explaining colour variation among animals at broad geographic scales remains challenging. Here we demonstrate how deep learning-a form of artificial i...
Despite advances in genotyping technologies, traditional kinship analysis tools utilized in forensic identification have seen limited evolution and la...
Current histological and anatomical analysis techniques, including fluorescence in situ hybridisation, immunohistochemistry, immunofluorescence, immun...
Identifying new indications for existing drugs may reduce costs and expedites drug development. Drug-related disease predictions typically combined he...
Reducing radiation dose is important for PET imaging. However, reducing injection doses causes increased image noise and low signal-to-noise ratio (SN...
Recently much effort has been invested in using convolutional neural network (CNN) models trained on 3D structural images of protein-ligand complexes ...
Sustainable urban development (SUD) requires a balance between economic growth, social well-being, and environmental protection. Oftentimes, urban pol...