Infectious Disease

Clinical evaluation of the GeneXpert® Xpert® Xpress SARS-CoV-2/Flu/RSV combination test.

The Cepheid Xpert Xpress SARS-CoV-2/Flu/RSV combination test received emergency use authorization approval by the United States Food and Drug Administration in December 2020, and Health Canada approval in January 2021. The performance characteristics of the GeneXpert Xpert Xpress SARS-CoV-2/Flu/RSV combination test were assessed at Lakeridge Health Oshawa and the National Microbiology Laboratory o...

Using Artificial Intelligence in Fungal Lung Disease: CPA CT Imaging as an Example.

This positioning paper aims to discuss current challenges and opportunities for artificial intelligence (AI) in fungal lung disease, with a focus on chronic pulmonary aspergillosis and some supporting proof-of-concept results using lung imaging. Given the high uncertainty in fungal infection diagnosis and analyzing treatment response, AI could potentially have an impactful role; however, developin...

Preventing sepsis; how can artificial intelligence inform the clinical decision-making process? A systematic review.

BACKGROUND AND OBJECTIVES: Sepsis is a life-threatening condition that is associated with increased mortality. Artificial intelligence tools can infor...

Artificial intelligence in the diagnosis of COVID-19: challenges and perspectives.

Artificial intelligence (AI) is being used to aid in various aspects of the COVID-19 crisis, including epidemiology, molecular research and drug devel...

Quantitative salivary gland SPECT/CT using deep convolutional neural networks.

Quantitative single-photon emission computed tomography/computed tomography (SPECT/CT) using Tc-99m pertechnetate aids in evaluating salivary gland fu...

Cystic cervical lymph nodes of papillary thyroid carcinoma, tuberculosis and human papillomavirus positive oropharyngeal squamous cell carcinoma: utility of deep learning in their differentiation on CT.

OBJECTIVES: Cervical lymph nodes with internal cystic changes are seen with several pathologies, including papillary thyroid carcinoma (PTC), tubercul...

Determinants of Tourism Stocks During the COVID-19: Evidence From the Deep Learning Models.

This paper examines the determinants of tourism stock returns in China from October 25, 2018, to October 21, 2020, including the COVID-19 era. We prop...

Classification Models for COVID-19 Test Prioritization in Brazil: Machine Learning Approach.

BACKGROUND: Controlling the COVID-19 outbreak in Brazil is a challenge due to the population's size and urban density, inefficient maintenance of soci...

Prediction of Streptococcus uberis clinical mastitis treatment success in dairy herds by means of mass spectrometry and machine-learning.

Streptococcus uberis is one of the leading pathogens causing mastitis worldwide. Identification of S. uberis strains that fail to respond to treatment...

Detection of COVID-19 from CT Lung Scans Using Transfer Learning.

This paper aims to investigate the use of transfer learning architectures in the detection of COVID-19 from CT lung scans. The study evaluates the per...

A Multimodality Machine Learning Approach to Differentiate Severe and Nonsevere COVID-19: Model Development and Validation.

BACKGROUND: Effectively and efficiently diagnosing patients who have COVID-19 with the accurate clinical type of the disease is essential to achieve o...

Identification of pediatric respiratory diseases using a fine-grained diagnosis system.

Respiratory diseases, including asthma, bronchitis, pneumonia, and upper respiratory tract infection (RTI), are among the most common diseases in clin...

Artificial Intelligence-Enabled Analysis of Public Attitudes on Facebook and Twitter Toward COVID-19 Vaccines in the United Kingdom and the United States: Observational Study.

BACKGROUND: Global efforts toward the development and deployment of a vaccine for COVID-19 are rapidly advancing. To achieve herd immunity, widespread...

Deep Transfer Learning Approach for Automatic Recognition of Drug Toxicity and Inhibition of SARS-CoV-2.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causes COVID-19 and is responsible for the ongoing pandemic. Screening of potential antiv...

CT-Based COVID-19 triage: Deep multitask learning improves joint identification and severity quantification.

The current COVID-19 pandemic overloads healthcare systems, including radiology departments. Though several deep learning approaches were developed to...

Ontology-driven weak supervision for clinical entity classification in electronic health records.

In the electronic health record, using clinical notes to identify entities such as disorders and their temporality (e.g. the order of an event relativ...

Development and Validation of a Machine Learning Model to Estimate Bacterial Sepsis Among Immunocompromised Recipients of Stem Cell Transplant.

IMPORTANCE: Sepsis disproportionately affects recipients of allogeneic hematopoietic cell transplant (allo-HCT), and timely detection is crucial. Howe...

Machine learning methods to predict mechanical ventilation and mortality in patients with COVID-19.

BACKGROUND: The Coronavirus disease 2019 (COVID-19) pandemic has affected millions of people across the globe. It is associated with a high mortality ...

Semi-supervised learning for an improved diagnosis of COVID-19 in CT images.

Coronavirus disease 2019 (COVID-19) has been spread out all over the world. Although a real-time reverse-transcription polymerase chain reaction (RT-P...

Classification and Design of HIV-1 Integrase Inhibitors Based on Machine Learning.

A key enzyme in human immunodeficiency virus type 1 (HIV-1) life cycle, integrase (IN) aids the integration of viral DNA into the host DNA, which has ...