Infectious Disease

Machine learning-assisted prediction of pneumonia based on non-invasive measures.

BACKGROUND: Pneumonia is an infection of the lungs that is characterized by high morbidity and mortality. The use of machine learning systems to detect respiratory diseases non-invasive measures such as physical and laboratory parameters is gaining momentum and has been proposed to decrease diagnostic uncertainty associated with bacterial pneumonia. Herein, this study conducted several experiment...

Automatic scoring of COVID-19 severity in X-ray imaging based on a novel deep learning workflow.

In this study, we propose a two-stage workflow used for the segmentation and scoring of lung diseases. The workflow inherits quantification, qualification, and visual assessment of lung diseases on X-ray images estimated by radiologists and clinicians. It requires the fulfillment of two core stages devoted to lung and disease segmentation as well as an additional post-processing stage devoted to s...

Clinically focused multi-cohort benchmarking as a tool for external validation of artificial intelligence algorithm performance in basic chest radiography analysis.

Artificial intelligence (AI) algorithms evaluating [supine] chest radiographs ([S]CXRs) have remarkably increased in number recently. Since training a...

An Empirical Analysis of an Optimized Pretrained Deep Learning Model for COVID-19 Diagnosis.

As a result of the COVID-19 outbreak, which has put the world in an unprecedented predicament, thousands of people have died. Data from structured and...

Combined Mueller matrix imaging and artificial intelligence classification framework for Hepatitis B detection.

SIGNIFICANCE: The combination of polarized imaging with artificial intelligence (AI) technology has provided a powerful tool for performing an objecti...

Machine learning in the loop for tuberculosis diagnosis support.

The use of machine learning (ML) for diagnosis support has advanced in the field of health. In the present paper, the results of studying ML technique...

A process mining- deep learning approach to predict survival in a cohort of hospitalized COVID-19 patients.

BACKGROUND: Various machine learning and artificial intelligence methods have been used to predict outcomes of hospitalized COVID-19 patients. However...

Deep Learning-Based Networks for Detecting Anomalies in Chest X-Rays.

X-ray images aid medical professionals in the diagnosis and detection of pathologies. They are critical, for example, in the diagnosis of pneumonia, t...

Multi-population generalizability of a deep learning-based chest radiograph severity score for COVID-19.

To tune and test the generalizability of a deep learning-based model for assessment of COVID-19 lung disease severity on chest radiographs (CXRs) from...

Nucleoside Triphosphate Hydrolases Assay in Toxoplasm gondii and Neospora caninum for High-Throughput Screening using a Robot Arm.

Protozoan parasites infect humans and many warm-blooded animals. Toxoplasma gondii, a major protozoan parasite, is commonly found in HIV-positive pati...

Technology Acceptance in Socially Assistive Robots: Scoping Review of Models, Measurement, and Influencing Factors.

OBJECTIVES: We summarized technology acceptance and the influencing factors of elderly people toward socially assistive robots (SARs).

Automated diagnosis and prognosis of COVID-19 pneumonia from initial ER chest X-rays using deep learning.

BACKGROUND: Airspace disease as seen on chest X-rays is an important point in triage for patients initially presenting to the emergency department wit...

Factors driving provider adoption of the TREWS machine learning-based early warning system and its effects on sepsis treatment timing.

Machine learning-based clinical decision support tools for sepsis create opportunities to identify at-risk patients and initiate treatments at early t...

The Use of Chest Radiographs and Machine Learning Model for the Rapid Detection of Pneumonitis in Pediatric.

Pneumonia is a common lung disease that is the leading cause of death worldwide. It primarily affects children, accounting for 18% of all deaths in ch...

Deep-learning-based removal of autofluorescence and fluorescence quantification in plant-colonizing bacteria in vivo.

Fluorescence microscopy is common in bacteria-plant interaction studies. However, strong autofluorescence from plant tissues impedes in vivo studies o...

Simplified Transfer Learning for Chest Radiography Models Using Less Data.

Background Developing deep learning models for radiology requires large data sets and substantial computational resources. Data set size limitations c...

An efficient deep learning-based framework for tuberculosis detection using chest X-ray images.

Early diagnosis of tuberculosis (TB) is an essential and challenging task to prevent disease, decrease mortality risk, and stop transmission to other ...

A Deep-Learning Based System for Rapid Genus Identification of Pathogens under Hyperspectral Microscopic Images.

Infectious diseases have always been a major threat to the survival of humanity. Additionally, they bring an enormous economic burden to society. The ...

Auxiliary Pneumonia Classification Algorithm Based on Pruning Compression.

Pneumonia infection is the leading cause of death in young children. The commonly used pneumonia detection method is that doctors diagnose through che...

Argument mining as rapid screening tool of COVID-19 literature quality: Preliminary evidence.

BACKGROUND: The COVID-19 pandemic prompted the scientific community to share timely evidence, also in the form of pre-printed papers, not peer reviewe...