COVID-19

Relational Modeling for Robust and Efficient Pulmonary Lobe Segmentation in CT Scans.

Pulmonary lobe segmentation in computed tomography scans is essential for regional assessment of pulmonary diseases. Recent works based on convolution neural networks have achieved good performance for this task. However, they are still limited in capturing structured relationships due to the nature of convolution. The shape of the pulmonary lobes affect each other and their borders relate to the ...

DeepCLIP: predicting the effect of mutations on protein-RNA binding with deep learning.

Nucleotide variants can cause functional changes by altering protein-RNA binding in various ways that are not easy to predict. This can affect processes such as splicing, nuclear shuttling, and stability of the transcript. Therefore, correct modeling of protein-RNA binding is critical when predicting the effects of sequence variations. Many RNA-binding proteins recognize a diverse set of motifs an...

Role of 5G-powered remote robotic ultrasound during the COVID-19 outbreak: insights from two cases.

The 2019 Novel Coronavirus disease (COVID-19) broke out in Wuhan, China in December 2019 and spread throughout the world. Early screening and early di...

Optimal Scree-CNN for Detecting NS1 Molecular Fingerprint from Salivary SERS Spectra.

Dengue fever (DF) is a viral infection with possible fatal consequence. NS1 is a recent antigen based biomarker for dengue fever (DF), as an alternati...

A Brain Tumor Segmentation Framework Based on Outlier Detection Using One-Class Support Vector Machine.

Accurate segmentation of brain tumors is a challenging task and also a crucial step in diagnosis and treatment planning for cancer patients. Magnetic ...

Deep Learning for Interictal Epileptiform Spike Detection from scalp EEG frequency sub bands.

Epilepsy diagnosis through visual examination of interictal epileptiform discharges (IEDs) in scalp electroencephalogram (EEG) signals is a challengin...

[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 public health emergency in human history. In a short p...

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 as an intervention mediator in a socio-emotional u...

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 the subtleties of joint biomechanics. Typically, the...

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 past 17 years, coronaviruses have triggered several o...

AI systems aim to sniff out coronavirus outbreaks.

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

Mobile microrobots offer great promise for minimally invasive targeted medical theranostic applications at hard-to-access regions inside the human bod...

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 proper function and the elimination of deleteriou...

[Artificial intelligence empowers laboratory medicine in Industry 4.0].

Since 2017, China, the United States, and the European Union have successively issued national-level artificial intelligence (AI) strategic developmen...

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 specificity and sparseness of the absolute incidence of ...

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 patients.   Based on the drug-gene interactions invo...

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 coronavirus 2019 disease (COVID-19), but quantita...

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

BACKGROUND: Molecular profiling has become essential for tumor risk stratification and treatment selection. However, cancer genome complexity and tech...