COVID-19

[Machine learning-based method for interpreting the guidelines of the diagnosis and treatment of COVID-19].

The outbreak of pneumonia caused by novel coronavirus (COVID-19) at the end of 2019 was a major publ...

Outcomes of a Robot-Assisted Social-Emotional Understanding Intervention for Young Children with Autism Spectrum Disorders.

This study is a randomized control trial aimed at testing the role of a human-assisted social robot ...

An Approach to Robotic Testing of the Wrist Using Three-Dimensional Imaging and a Hybrid Testing Methodology.

Robotic technology is increasingly used for sophisticated in vitro testing designed to understand th...

Coronavirus Disease (COVID-19): A Machine Learning Bibliometric Analysis.

BACKGROUND/AIM: To evaluate the research trends in coronavirus disease (COVID-19).

Analysis of knowledge bases and research hotspots of coronavirus from the perspective of mapping knowledge domain.

BACKGROUND: Coronaviruses have drawn attention since the beginning of the 21st century. Over the pas...

Multifunctional surface microrollers for targeted cargo delivery in physiological blood flow.

Mobile microrobots offer great promise for minimally invasive targeted medical theranostic applicati...

Deep Learning Localization of Pneumonia: 2019 Coronavirus (COVID-19) Outbreak.

Antibody complementarity determining region design using high-capacity machine learning.

MOTIVATION: The precise targeting of antibodies and other protein therapeutics is required for their...

[Artificial intelligence empowers laboratory medicine in Industry 4.0].

Since 2017, China, the United States, and the European Union have successively issued national-level...

Highly accurate and explainable detection of specimen mix-up using a machine learning model.

Background Delta check is widely used for detecting specimen mix-ups. Owing to the inadequate specif...

Evaluation of clinical impact of pharmacogenomics knowledge involved in CPIC guidelines on Chinese pediatric patients.

To evaluate the clinical benefits of implementing pharmacogenomics testing for Chinese pediatric pa...

AI-Driven COVID-19 Tools to Interpret, Quantify Lung Images.

Qualitative interpretation is a good thing when it comes to reading lung images in the fight against...

Using Machine Learning to Identify True Somatic Variants from Next-Generation Sequencing.

BACKGROUND: Molecular profiling has become essential for tumor risk stratification and treatment sel...

Antibody Clustering Using a Machine Learning Pipeline that Fuses Genetic, Structural, and Physicochemical Properties.

Antibody V domain clustering is of paramount importance to a repertoire of immunology-related areas....

Identification of COVID-19 samples from chest X-Ray images using deep learning: A comparison of transfer learning approaches.

BACKGROUND: The novel coronavirus disease 2019 (COVID-19) constitutes a public health emergency glob...

Detection of coronavirus disease from X-ray images using deep learning and transfer learning algorithms.

OBJECTIVE: This study aims to employ the advantages of computer vision and medical image analysis to...

Convolutional neural network model to predict causal risk factors that share complex regulatory features.

Major progress in disease genetics has been made through genome-wide association studies (GWASs). On...

Deep Learning Reveals Cancer Metastasis and Therapeutic Antibody Targeting in the Entire Body.

Reliable detection of disseminated tumor cells and of the biodistribution of tumor-targeting therape...

Functional interpretation of genetic variants using deep learning predicts impact on chromatin accessibility and histone modification.

Identifying functional variants underlying disease risk and adoption of personalized medicine are cu...

Machine-learned analysis of the association of next-generation sequencing-based genotypes with persistent pain after breast cancer surgery.

Cancer and its surgical treatment are among the most important triggering events for persistent pain...

Artificial Intelligence Estimates the Importance of Baseline Factors in Predicting Response to Anti-PD1 in Metastatic Melanoma.

OBJECTIVE: Prognosis of patients with metastatic melanoma has dramatically improved over recent year...