Infectious Disease

Deep Learning Models to Predict Fatal Pneumonia Using Chest X-Ray Images.

BACKGROUND AND AIMS: Chest X-ray (CXR) is indispensable to the assessment of severity, diagnosis, and management of pneumonia. Deep learning is an artificial intelligence (AI) technology that has been applied to the interpretation of medical images. This study investigated the feasibility of classifying fatal pneumonia based on CXR images using deep learning models on publicly available platforms.

Objectivization of virus titration method in GMP-regulated environment using artificial intelligence-based classification system.

The implementation of artificial intelligence-based systems (AI) into highly regulated industries faces significant regulatory and logistical challenges. The lack of established practices and guidelines, risk aversion attitude, perception of AI technology as insufficiently tested and unreliable are among the most important factors preventing wider adoption of AI solutions into pharmaceutical indus...

A multistage multimodal deep learning model for disease severity assessment and early warnings of high-risk patients of COVID-19.

The outbreak of coronavirus disease 2019 (COVID-19) has caused massive infections and large death tolls worldwide. Despite many studies on the clinica...

An optimistic firefly algorithm-based deep learning approach for sentiment analysis of COVID-19 tweets.

The unprecedented rise in the number of COVID-19 cases has drawn global attention, as it has caused an adverse impact on the lives of people all over ...

Deep Learning-Based Computer-Aided Diagnosis (CAD): Applications for Medical Image Datasets.

Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the...

Identification of hospitalized mortality of patients with COVID-19 by machine learning models based on blood inflammatory cytokines.

Coronavirus disease 2019 (COVID-19) spread worldwide and presented a significant threat to people's health. Inappropriate disease assessment and treat...

Calibrated bagging deep learning for image semantic segmentation: A case study on COVID-19 chest X-ray image.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19). Imaging tests such as chest X-ray (CXR) and c...

Musculoskeletal radiologist-level performance by using deep learning for detection of scaphoid fractures on conventional multi-view radiographs of hand and wrist.

OBJECTIVES: To assess how an artificial intelligence (AI) algorithm performs against five experienced musculoskeletal radiologists in diagnosing scaph...

Application of machine and deep learning algorithms in optical microscopic detection of Plasmodium: A malaria diagnostic tool for the future.

Machine and deep learning techniques are prevalent in the medical discipline due to their high level of accuracy in disease diagnosis. One such diseas...

P-ResUnet: Segmentation of brain tissue with Purified Residual Unet.

Brain tissue of Magnetic Resonance Imaging is precisely segmented and quantified, which aids in the diagnosis of neurological diseases such as epileps...

Diagnostic performance of machine learning models using cell population data for the detection of sepsis: a comparative study.

OBJECTIVES: To compare the artificial intelligence algorithms as powerful machine learning methods for evaluating patients with suspected sepsis using...

The Health Gym: synthetic health-related datasets for the development of reinforcement learning algorithms.

In recent years, the machine learning research community has benefited tremendously from the availability of openly accessible benchmark datasets. Cli...

Transit communication via Twitter during the COVID-19 pandemic.

Transit providers have used social media (e.g., Twitter) as a powerful platform to shape public perception and provide essential information, especial...

Generative adversarial network based data augmentation for CNN based detection of Covid-19.

Covid-19 has been a global concern since 2019, crippling the world economy and health. Biological diagnostic tools have since been developed to identi...

Reinforcement Learning Based Diagnosis and Prediction for COVID-19 by Optimizing a Mixed Cost Function From CT Images.

A novel coronavirus disease (COVID-19) is a pandemic disease has caused 4 million deaths and more than 200 million infections worldwide (as of August ...

MFL-Net: An Efficient Lightweight Multi-Scale Feature Learning CNN for COVID-19 Diagnosis From CT Images.

Timely and accurate diagnosis of coronavirus disease 2019 (COVID-19) is crucial in curbing its spread. Slow testing results of reverse transcription-p...

Ferrobotic swarms enable accessible and adaptable automated viral testing.

Expanding our global testing capacity is critical to preventing and containing pandemics. Accordingly, accessible and adaptable automated platforms th...

NAVIGATOR: an Italian regional imaging biobank to promote precision medicine for oncologic patients.

NAVIGATOR is an Italian regional project boosting precision medicine in oncology with the aim of making it more predictive, preventive, and personalis...

Pharmacological, Non-Pharmacological Policies and Mutation: An Artificial Intelligence Based Multi-Dimensional Policy Making Algorithm for Controlling the Casualties of the Pandemic Diseases.

Fighting against the pandemic diseases with unique characters requires new sophisticated approaches like the artificial intelligence. This paper devel...

COVID-19 classification using chest X-ray images based on fusion-assisted deep Bayesian optimization and Grad-CAM visualization.

The COVID-19 virus's rapid global spread has caused millions of illnesses and deaths. As a result, it has disastrous consequences for people's lives, ...