Infectious Disease

Automatic Deep Learning Segmentation and Quantification of Epicardial Adipose Tissue in Non-Contrast Cardiac CT scans.

An Automatic deep learning semantic segmentation (ADLS) using DeepLab-v3-plus technique is proposed for a full and accurate whole heart Epicardial adipose tissue (EAT) segmentation from non-contrast cardiac CT scan. The ADLS algorithm was trained on manual segmented scans of the enclosed region of the pericardium (sac), which represents the internal heart tissues where the EAT is located. A level ...

TDA-Net: Fusion of Persistent Homology and Deep Learning Features for COVID-19 Detection From Chest X-Ray Images.

Topological Data Analysis (TDA) has emerged recently as a robust tool to extract and compare the structure of datasets. TDA identifies features in data (e.g., connected components and holes) and assigns a quantitative measure to these features. Several studies reported that topological features extracted by TDA tools provide unique information about the data, discover new insights, and determine w...

Design of Novel End-effectors for Robot-assisted Swab Sampling to Combat Respiratory Infectious Diseases.

The COVID-19 outbreak has caused the mortality worldwide and the use of swab sampling is a common way of screening and diagnosis. To combat respirator...

A disposable force regulation mechanism for throat swab robot.

Robots can protect healthcare workers from being infected by the COVID-19 and play a role in throat swab sampling operation. A critical requirement in...

Deep Learning Assisted Microfluidic Impedance Flow Cytometry for Label-free Foodborne Bacteria Analysis and Classification.

According to the urgent need for rapid detection and identification of foodborne bacteria to prevent public health event, a microfluidic electrical im...

Regulation Modelling and Analysis Using Machine Learning During the Covid-19 Pandemic in Russia.

Due to the specific circumstances related to the COVID-19 pandemic, many countries have enforced emergency measures such as self-isolation and restric...

Factors determining generalization in deep learning models for scoring COVID-CT images.

The COVID-19 pandemic has inspired unprecedented data collection and computer vision modelling efforts worldwide, focused on the diagnosis of COVID-19...

Computational prediction of the effect of amino acid changes on the binding affinity between SARS-CoV-2 spike RBD and human ACE2.

The association of the receptor binding domain (RBD) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein with human angioten...

Detection and characterization of COVID-19 findings in chest CT: Feasibility and applicability of an AI-based software tool.

The COVID-19 pandemic has challenged institutions' diagnostic processes worldwide. The aim of this study was to assess the feasibility of an artificia...

Cohort-Derived Machine Learning Models for Individual Prediction of Chronic Kidney Disease in People Living With Human Immunodeficiency Virus: A Prospective Multicenter Cohort Study.

BACKGROUND: It is unclear whether data-driven machine learning models, which are trained on large epidemiological cohorts, may improve prediction of c...

Are small airplanes safe with regards to COVID-19 transmission?

Social distancing is impossible in small aircrafts but there is a specific, highly effective ventilation system. Measurements proved that there is no ...

Photodynamic Therapy Using Toluidine Blue O (TBO) Dye as a Photosensitizer against .

BACKGROUND: Photodynamic therapy (PDT) is alternative treatment of cutaneous leishmaniasis (CL), and phenolthiazine dyes such as Toluidine Blue O (TBO...

CoCoNet: an efficient deep learning tool for viral metagenome binning.

MOTIVATION: Metagenomic approaches hold the potential to characterize microbial communities and unravel the intricate link between the microbiome and ...

Deep learning identifies synergistic drug combinations for treating COVID-19.

Effective treatments for COVID-19 are urgently needed. However, discovering single-agent therapies with activity against severe acute respiratory synd...

Application of machine learning in CT images and X-rays of COVID-19 pneumonia.

Coronavirus disease (COVID-19) has spread worldwide. X-ray and computed tomography (CT) are 2 technologies widely used in image acquisition, segmentat...

Machine learning and applications in microbiology.

To understand the intricacies of microorganisms at the molecular level requires making sense of copious volumes of data such that it may now be humanl...

A reinforcement learning model to inform optimal decision paths for HIV elimination.

The 'Ending the HIV Epidemic (EHE)' national plan aims to reduce annual HIV incidence in the United States from 38,000 in 2015 to 9300 by 2025 and 330...

Accurate prediction of multi-label protein subcellular localization through multi-view feature learning with RBRL classifier.

Multi-label proteins can participate in carrier transportation, enzyme catalysis, hormone regulation and other life activities. Meanwhile, they play a...

Current status and future perspectives of computational studies on human-virus protein-protein interactions.

The protein-protein interactions (PPIs) between human and viruses mediate viral infection and host immunity processes. Therefore, the study of human-v...

Comprehensive assessment of machine learning-based methods for predicting antimicrobial peptides.

Antimicrobial peptides (AMPs) are a unique and diverse group of molecules that play a crucial role in a myriad of biological processes and cellular fu...