Infectious Disease

Comparison of machine learning methods for estimating case fatality ratios: An Ebola outbreak simulation study.

BACKGROUND: Machine learning (ML) algorithms are now increasingly used in infectious disease epidemiology. Epidemiologists should understand how ML algorithms behave within the context of outbreak data where missingness of data is almost ubiquitous.

Artificial intelligence approach towards assessment of condition of COVID-19 patients - Identification of predictive biomarkers associated with severity of clinical condition and disease progression.

BACKGROUND AND OBJECTIVES: Although ML has been studied for different epidemiological and clinical issues as well as for survival prediction of COVID-19, there is a noticeable shortage of literature dealing with ML usage in prediction of disease severity changes through the course of the disease. In that way, predicting disease progression from mild towards moderate, severe and critical condition,...

Predicting clinical outcomes in COVID-19 using radiomics on chest radiographs.

OBJECTIVES: For optimal utilization of healthcare resources, there is a critical need for early identification of COVID-19 patients at risk of poor pr...

Application of green synthesised copper iodide particles on cotton fabric-protective face mask material against COVID-19 pandemic.

Microorganisms cause variety of diseases that constitutes a severe threat to mankind. Due to the upsurge of many infectious diseases, there is a high ...

SIRVD-DL: A COVID-19 deep learning prediction model based on time-dependent SIRVD.

COVID-19 is one of the biggest challenges that human beings have faced recently. Many researchers have proposed different prediction methods for estab...

In-hospital Outcomes of Infective Endocarditis from 1978 to 2015: Analysis Through Machine-Learning Techniques.

BACKGROUND: Early identification of patients with infective endocarditis (IE) at higher risk for in-hospital mortality is essential to guide managemen...

Design of a Reconfigurable Wall Disinfection Robot.

During a viral outbreak, such as COVID-19, autonomously operated robots are in high demand. Robots effectively improve the environmental concerns of c...

A Novel Smart City-Based Framework on Perspectives for Application of Machine Learning in Combating COVID-19.

The spread of COVID-19 worldwide continues despite multidimensional efforts to curtail its spread and provide treatment. Efforts to contain the COVID-...

Repurposing non-oncology small-molecule drugs to improve cancer therapy: Current situation and future directions.

Drug repurposing or repositioning has been well-known to refer to the therapeutic applications of a drug for another indication other than it was orig...

DR-MIL: deep represented multiple instance learning distinguishes COVID-19 from community-acquired pneumonia in CT images.

BACKGROUND AND OBJECTIVE: Given that the novel coronavirus disease 2019 (COVID-19) has become a pandemic, a method to accurately distinguish COVID-19 ...

Submerged fermentation improves bioactivity of mulberry fruits and leaves.

OBJECTIVE: Mulberry ( spp.) fruits and leaves have been proven to possess nutraceutical properties. Due to its fast and easy growing characteristics, ...

Automated machine learning for endemic active tuberculosis prediction from multiplex serological data.

Serological diagnosis of active tuberculosis (TB) is enhanced by detection of multiple antibodies due to variable immune responses among patients. Cli...

Diagnostic classification of coronavirus disease 2019 (COVID-19) and other pneumonias using radiomics features in CT chest images.

We propose a classification method using the radiomics features of CT chest images to identify patients with coronavirus disease 2019 (COVID-19) and o...

Accelerating antibiotic discovery through artificial intelligence.

By targeting invasive organisms, antibiotics insert themselves into the ancient struggle of the host-pathogen evolutionary arms race. As pathogens evo...

Machine Learning augmented docking studies of aminothioureas at the SARS-CoV-2-ACE2 interface.

The current pandemic outbreak clearly indicated the urgent need for tools allowing fast predictions of bioactivity of a large number of compounds, eit...

Kefir modulates gut microbiota and reduces DMH-associated colorectal cancer via regulation of intestinal inflammation in adulthood offsprings programmed by neonatal overfeeding.

Obesity is associated with chronic inflammation, intestinal dysbiosis, and colorectal cancer risk. The anti-cancer effects of kefir are highlighted. H...

Machine-learning-based COVID-19 mortality prediction model and identification of patients at low and high risk of dying.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic caused by the SARS-Cov2 virus has become the greatest health and controversial issue for ...

Mobile microscopy and telemedicine platform assisted by deep learning for the quantification of Trichuris trichiura infection.

Soil-transmitted helminths (STH) are the most prevalent pathogens among the group of neglected tropical diseases (NTDs). The Kato-Katz technique is th...

Literature Mining and Mechanistic Graphical Modelling to Improve mRNA Vaccine Platforms.

RNA vaccines represent a milestone in the history of vaccinology. They provide several advantages over more traditional approaches to vaccine developm...

Applying a novel approach to scoping review incorporating artificial intelligence: mapping the natural history of gonorrhoea.

BACKGROUND: Systematic and scoping literature searches are increasingly resource intensive. We present the results of a scoping review which combines ...