Surveillance

OutbreakFlow: Model-based Bayesian inference of disease outbreak dynamics with invertible neural networks and its application to the COVID-19 pandemics in Germany.

Mathematical models in epidemiology are an indispensable tool to determine the dynamics and important characteristics of infectious diseases. Apart from their scientific merit, these models are often used to inform political decisions and interventional measures during an ongoing outbreak. However, reliably inferring the epidemical dynamics by connecting complex models to real data is still hard a...

Artificial Intelligence Applications in Urology: Reporting Standards to Achieve Fluency for Urologists.

The growth and adoption of artificial intelligence has led to impressive results in urology. As artificial intelligence grows more ubiquitous, it is important to establish artificial intelligence literacy in the workforce. To this end, we present a narrative review of the literature of artificial intelligence and machine learning in urology and propose a checklist of reporting standards to improve...

Machine learning and artificial intelligence: applications in healthcare epidemiology.

Artificial intelligence (AI) refers to the performance of tasks by machines ordinarily associated with human intelligence. Machine learning (ML) is a ...

Deep Learning for Automated Triaging of 4581 Breast MRI Examinations from the DENSE Trial.

Background Supplemental screening with MRI has proved beneficial in women with extremely dense breasts. Most MRI examinations show normal anatomic and...

The Use and Performance of Artificial Intelligence in Prosthodontics: A Systematic Review.

(1) Background: The rapid pace of digital development in everyday life is also reflected in dentistry, including the emergence of the first systems ba...

PM₂.₅ Monitoring: Use Information Abundance Measurement and Wide and Deep Learning.

This article devises a photograph-based monitoring model to estimate the real-time PM concentrations, overcoming currently popular electrochemical sen...

[Structured reporting and artificial intelligence].

BACKGROUND: There are a multitude of application possibilities of artificial intelligence (AI) and structured reporting (SR) in radiology. The number ...

The reporting quality of natural language processing studies: systematic review of studies of radiology reports.

BACKGROUND: Automated language analysis of radiology reports using natural language processing (NLP) can provide valuable information on patients' hea...

Perspectives: A surgeon's guide to machine learning.

The exponential increase in the volume and complexity of healthcare data presents new challenges to researchers and clinicians in analysis and interpr...

Comparing classification models-a practical tutorial.

While machine learning models have become a mainstay in Cheminformatics, the field has yet to agree on standards for model evaluation and comparison. ...

Incorporating metadata in HIV transmission network reconstruction: A machine learning feasibility assessment.

HIV molecular epidemiology estimates the transmission patterns from clustering genetically similar viruses. The process involves connecting geneticall...

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 al...

A Comprehensive Review of Techniques for Processing and Analyzing Fetal Heart Rate Signals.

The availability of standardized guidelines regarding the use of electronic fetal monitoring (EFM) in clinical practice has not effectively helped to ...

Machine Learning for Real-Time Heart Disease Prediction.

Heart-related anomalies are among the most common causes of death worldwide. Patients are often asymptomatic until a fatal event happens, and even whe...

Systematic Review of the Effectiveness of Machine Learning Algorithms for Classifying Pain Intensity, Phenotype or Treatment Outcomes Using Electroencephalogram Data.

Recent attempts to utilize machine learning (ML) to predict pain-related outcomes from Electroencephalogram (EEG) data demonstrate promising results. ...

Estimating the conditional probability of developing human papilloma virus related oropharyngeal cancer by combining machine learning and inverse Bayesian modelling.

The epidemic increase in the incidence of Human Papilloma Virus (HPV) related Oropharyngeal Squamous Cell Carcinomas (OPSCCs) in several countries wor...

A mechatronics data collection, image processing, and deep learning platform for clinical posture analysis: a technical note.

Static and dynamic posture analysis was a critical clinical examination in physiotherapy and rehabilitation. It was a time-consuming task for clinicia...

A machine learning approach identifies 5-ASA and ulcerative colitis as being linked with higher COVID-19 mortality in patients with IBD.

Inflammatory bowel diseases (IBD), namely Crohn's disease (CD) and ulcerative colitis (UC) are chronic inflammation within the gastrointestinal tract....

Mammographic Surveillance After Breast-Conserving Therapy: Impact of Digital Breast Tomosynthesis and Artificial Intelligence-Based Computer-Aided Detection.

Postoperative mammograms present interpretive challenges due to postoperative distortion and hematomas. The application of digital breast tomosyn-the...

Chronic kidney disease diagnosis using decision tree algorithms.

BACKGROUND: Chronic Kidney Disease (CKD), i.e., gradual decrease in the renal function spanning over a duration of several months to years without any...