AIMC Topic: Humans

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Artificial intelligence-aided clinical annotation of a large multi-cancer genomic dataset.

Nature communications
To accelerate cancer research that correlates biomarkers with clinical endpoints, methods are needed to ascertain outcomes from electronic health records at scale. Here, we train deep natural language processing (NLP) models to extract outcomes for p...

Ghost in the machine or monkey with a typewriter-generating titles for Christmas research articles in using artificial intelligence: observational study.

BMJ (Clinical research ed.)
OBJECTIVE: To determine whether artificial intelligence (AI) can generate plausible and engaging titles for potential Christmas research articles in .

Primal-dual for classification with rejection (PD-CR): a novel method for classification and feature selection-an application in metabolomics studies.

BMC bioinformatics
BACKGROUND: Supervised classification methods have been used for many years for feature selection in metabolomics and other omics studies. We developed a novel primal-dual based classification method (PD-CR) that can perform classification with rejec...

Prediction of solar cell materials via unsupervised literature learning.

Journal of physics. Condensed matter : an Institute of Physics journal
Despite the significant advancement of the data-driven studies for physical science, the textual data that are numerous in the literature are not fully embraced by the physics and materials community. In this manuscript, we successfully employ the na...

Data Centric Molecular Analysis and Evaluation of Hepatocellular Carcinoma Therapeutics Using Machine Intelligence-Based Tools.

Journal of gastrointestinal cancer
PURPOSE: Computational approaches have been used at different stages of drug development with the purpose of decreasing the time and cost of conventional experimental procedures. Lately, techniques mainly developed and applied in the field of artific...

Magnetic Resonance Imaging Images under Deep Learning in the Identification of Tuberculosis and Pneumonia.

Journal of healthcare engineering
This work aimed to explore the application value of deep learning-based magnetic resonance imaging (MRI) images in the identification of tuberculosis and pneumonia, in order to provide a certain reference basis for clinical identification. In this st...

Spine Medical Image Segmentation Based on Deep Learning.

Journal of healthcare engineering
The aim was to further explore the clinical value of deep learning algorithm in the field of spinal medical image segmentation, and this study designed an improved U-shaped network (BN-U-Net) algorithm and applied it to the spinal MRI medical image s...

D2-CovidNet: A Deep Learning Model for COVID-19 Detection in Chest X-Ray Images.

Computational intelligence and neuroscience
Since the outbreak of Coronavirus disease 2019 (COVID-19), it has been spreading rapidly worldwide and has not yet been effectively controlled. Many researchers are studying novel Coronavirus pneumonia from chest X-ray images. In order to improve the...

Assessing the reliability of automatic sentiment analysis tools on rating the sentiment of reviews of NHS dental practices in England.

PloS one
BACKGROUND: Online reviews may act as a rich source of data to assess the quality of dental practices. Assessing the content and sentiment of reviews on a large scale is time consuming and expensive. Automation of the process of assigning sentiment t...