Infectious Disease

Network-principled deep generative models for designing drug combinations as graph sets.

MOTIVATION: Combination therapy has shown to improve therapeutic efficacy while reducing side effects. Importantly, it has become an indispensable strategy to overcome resistance in antibiotics, antimicrobials and anticancer drugs. Facing enormous chemical space and unclear design principles for small-molecule combinations, computational drug-combination design has not seen generative models to me...

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 diagnosis play key roles in prevention and management of the epidemic. Attention should also be paid to the infection of health workers and shortage of medical resources in high-risk areas. Here, we report two cases of patients diagnosed with COVID-19 ...

A novel approach for remote detection of bacteria using simple charge-coupled device cameras and telescope.

We have designed, constructed, and utilized a charge-coupled device system, integrated with a small Newtonian telescope, capable of long distance reco...

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...

Potential Prognostic Markers in the Heart Rate Variability Features for Early Diagnosis of Sepsis in the Pediatric Intensive Care Unit using Convolutional Neural Network Classifiers.

Blood infection due to different circumstances could immediately develop to an extreme body reaction that leads to a serious life-threatening conditio...

Multi-View Ensemble Convolutional Neural Network to Improve Classification of Pneumonia in Low Contrast Chest X-Ray Images.

Pneumonia is one of the leading causes of childhood mortality worldwide. Chest x-ray (CXR) can aid the diagnosis of pneumonia, but in the case of low ...

A Study on Tuberculosis Classification in Chest X-ray Using Deep Residual Attention Networks.

The introduction of deep learning techniques for the computer-aided detection scheme has shed a light for real incorporation into the clinical workflo...

Deep transfer learning for video-based detection of newborn presence in incubator.

Preterm newborns are prone to late-onset sepsis, leading to a high risk of mortality. Video-based analysis of motion is a promising non-invasive appro...

Classifying Pneumonia among Chest X-Rays Using Transfer Learning.

Chest radiography has become the modality of choice for diagnosing pneumonia. However, analyzing chest X-ray images may be tedious, time-consuming and...

The efficacy of support vector machines in modelling deviations from the Beer-Lambert law for optical measurement of lactate.

Lactate is an important biomarker with a significant diagnostic and prognostic ability in relation to life-threatening conditions and diseases such as...

Practical Machine Learning-Based Sepsis Prediction.

Sepsis is a life-threatening clinical syndrome and one of the most expensive conditions treated in hospitals. It is challenging to detect due to the n...

Assisting the Non-invasive Diagnosis of Liver Fibrosis Stages using Machine Learning Methods.

Fibrosis is a significant indication of chronic liver diseases often due to hepatitis C Virus. It is becoming a global concern as a result of the rapi...

Potential Prognostic Markers in the Heart Rate Variability Features for Early Diagnosis of Sepsis in the Pediatric Intensive Care Unit using Convolutional Neural Network Classifiers.

Blood infection due to different circumstances could immediately develop to an extreme body reaction that leads to a serious life-threatening conditio...

Unsupervised Machine Learning for the Discovery of Latent Clusters in COVID-19 Patients Using Electronic Health Records.

The goal of this paper was to apply unsupervised machine learning techniques towards the discovery of latent clusters in COVID-19 patients. Over 6,000...

Using Machine Learning Algorithms to Predict Antimicrobial Resistance and Assist Empirical Treatment.

Multi-drug-resistant (MDR) infections and their devastating consequences constitute a global problem and a constant threat to public health with immen...

An Efficient Method to Predict Pneumonia from Chest X-Rays Using Deep Learning Approach.

Pneumonia is a severe health problem causing millions of deaths every year. The aim of this study was to develop an advanced deep learning-based archi...

[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...

Field performance of sterile male mosquitoes released from an uncrewed aerial vehicle.

Genetic control methods of mosquito vectors of malaria, dengue, yellow fever, and Zika are becoming increasingly popular due to the limitations of oth...

Enzyme-powered Janus platelet cell robots for active and targeted drug delivery.

Transforming natural cells into functional biocompatible robots capable of active movement is expected to enhance the functions of the cells and revol...

The Parasitic Nature of Social AI: Sharing Minds with the Mindless.

Can artificial intelligence (AI) develop the potential to be our partner, and will we be as sensitive to its social signals as we are to those of huma...