Infectious Disease

Construction and validation of a machine learning-based nomogram: A tool to predict the risk of getting severe coronavirus disease 2019 (COVID-19).

BACKGROUND: Identifying patients who may develop severe coronavirus disease 2019 (COVID-19) will facilitate personalized treatment and optimize the distribution of medical resources.

Automatic Classification of Hepatic Cystic Echinococcosis Using Ultrasound Images and Deep Learning.

BACKGROUND: Hepatic cystic echinococcosis is the main form of hepatic echinococcosis, which is a life-threatening liver disease caused by parasites that requires a precise diagnosis and proper treatment.

Artificial Intelligence-Aided Precision Medicine for COVID-19: Strategic Areas of Research and Development.

Artificial intelligence (AI) technologies can play a key role in preventing, detecting, and monitoring epidemics. In this paper, we provide an overvie...

Antimicrobial Activity of Necklace Orchids is Phylogenetically Clustered and can be Predicted With a Biological Response Method.

Necklace orchids (Coelogyninae, Epidendroideae) have been used in traditional medicine practices for centuries. Previous studies on a subset of unrela...

Accelerated antimicrobial discovery via deep generative models and molecular dynamics simulations.

The de novo design of antimicrobial therapeutics involves the exploration of a vast chemical repertoire to find compounds with broad-spectrum potency ...

Exploring the effect of image enhancement techniques on COVID-19 detection using chest X-ray images.

Computer-aided diagnosis for the reliable and fast detection of coronavirus disease (COVID-19) has become a necessity to prevent the spread of the vir...

Deep learning for diagnosis of COVID-19 using 3D CT scans.

A new pneumonia-type coronavirus, COVID-19, recently emerged in Wuhan, China. COVID-19 has subsequently infected many people and caused many deaths wo...

Synthesis and antimicrobial activities of chitosan/polypropylene carbonate-based nanoparticles.

Antibiotic resistance is an emerging threat to public health. The development of a new generation of antimicrobial compounds is therefore currently re...

Feasibility of ultraviolet light-emitting diode irradiation robot for terminal decontamination of coronavirus disease 2019 (COVID-19) patient rooms.

OBJECTIVE: To investigate the feasibility of using an ultraviolet light-emitting diode (UV LED) robot for the terminal decontamination of coronavirus ...

Prediction of the duration needed to achieve culture negativity in patients with active pulmonary tuberculosis using convolutional neural networks and chest radiography.

BACKGROUND: We aimed to predict the duration needed to achieve culture negativity in patients with active pulmonary tuberculosis using convolutional n...

Machine Learning-Based Prediction of COVID-19 Severity and Progression to Critical Illness Using CT Imaging and Clinical Data.

OBJECTIVE: To develop a machine learning (ML) pipeline based on radiomics to predict Coronavirus Disease 2019 (COVID-19) severity and the future deter...

Reservoir hosts prediction for COVID-19 by hybrid transfer learning model.

The recent outbreak of COVID-19 has infected millions of people around the world, which is leading to the global emergency. In the event of the virus ...

Abnormal lung quantification in chest CT images of COVID-19 patients with deep learning and its application to severity prediction.

OBJECTIVE: Computed tomography (CT) provides rich diagnosis and severity information of COVID-19 in clinical practice. However, there is no computeriz...

Machine learning models to identify low adherence to influenza vaccination among Korean adults with cardiovascular disease.

BACKGROUND: Annual influenza vaccination is an important public health measure to prevent influenza infections and is strongly recommended for cardiov...

Towards in silico Process Modeling for Vaccines.

Chemical, manufacturing, and control development timelines occupy a significant part of vaccine end-to-end development. In the on-going race for accel...

DeepVISP: Deep Learning for Virus Site Integration Prediction and Motif Discovery.

Approximately 15% of human cancers are estimated to be attributed to viruses. Virus sequences can be integrated into the host genome, leading to genom...

A Comprehensive Overview of the COVID-19 Literature: Machine Learning-Based Bibliometric Analysis.

BACKGROUND: Shortly after the emergence of COVID-19, researchers rapidly mobilized to study numerous aspects of the disease such as its evolution, cli...

COVID-19 in early 2021: current status and looking forward.

Since the first description of a coronavirus-related pneumonia outbreak in December 2019, the virus SARS-CoV-2 that causes the infection/disease (COVI...

Machine-learning model led design to experimentally test species thermal limits: The case of kissing bugs (Triatominae).

Species Distribution Modelling (SDM) determines habitat suitability of a species across geographic areas using macro-climatic variables; however, micr...

PSSPNN: PatchShuffle Stochastic Pooling Neural Network for an Explainable Diagnosis of COVID-19 with Multiple-Way Data Augmentation.

AIM: COVID-19 has caused large death tolls all over the world. Accurate diagnosis is of significant importance for early treatment.