Public Health & Policy

Does adoption of new technology increase surgical volume? The robotic inguinal hernia repair model.

Robotic Inguinal Hernia repair has been associated with higher costs but shorter length of stay. Robotic surgery is an appealing option for patients undergoing elective hernia surgery however given the high startup, maintenance and operating costs, the adoption of robotic technology may not guarantee increased profitability. Our hypothesis is that the introduction of robotic technology increases t...

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 solve the main drawbacks of fetal heart rate (FHR) surveillance methodology, which still presents inter- and intra-observer variability as well as uncertainty in the classification of unreassuring or risky FHR recordings. Given the clinical relevance...

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...

[Artificial Intelligence and teleradiology in cardiovascular imaging by CT-Scan and MRI].

Cardiac CT-Scan and cardiac magnetic resonance imaging (MRI) are two booming cardiac imaging modalities especially in chest pain screening for CT-Scan...

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...

Predicting Future Service Use in Dutch Mental Healthcare: A Machine Learning Approach.

A mental healthcare system in which the scarce resources are equitably and efficiently allocated, benefits from a predictive model about expected serv...

Investigating yielding behavior of heterogeneous vehicles at a semi-controlled crosswalk.

It is well known that pedestrians are vulnerable road users. Their risk of being injured or killed in road traffic crashes is even higher as vehicle d...

Artificial Intelligence for Identifying the Prevention of Medication Incidents Causing Serious or Moderate Harm: An Analysis Using Incident Reporters' Views.

The purpose of this study was to describe incident reporters' views identified by artificial intelligence concerning the prevention of medication inci...

Detection of COVID-19 Using Transfer Learning and Grad-CAM Visualization on Indigenously Collected X-ray Dataset.

The COVID-19 outbreak began in December 2019 and has dreadfully affected our lives since then. More than three million lives have been engulfed by thi...

Predicting spatiotemporally-resolved mean air temperature over Sweden from satellite data using an ensemble model.

Mapping of air temperature (Ta) at high spatiotemporal resolution is critical to reducing exposure assessment errors in epidemiological studies on the...

The Increasing Centrality of Robotic Technology in the Context of Nursing Care: Bioethical Implications Analyzed through a Scoping Review Approach.

At the dawn of the fourth industrial revolution, the healthcare industry is experiencing a momentous shift in the direction of increasingly pervasive ...

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...

Piezoelectric Smart Patch Operated with Machine-Learning Algorithms for Effective Detection and Elimination of Condensation.

Timely detection and elimination of surface condensation is crucial for diverse applications in agriculture, automotive, oil and gas industries, and r...

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...

Machine Learning Approach for Active Vaccine Safety Monitoring.

BACKGROUND: Vaccine safety surveillance is important because it is related to vaccine hesitancy, which affects vaccination rate. To increase confidenc...

Deep learning and lung ultrasound for Covid-19 pneumonia detection and severity classification.

The Covid-19 European outbreak in February 2020 has challenged the world's health systems, eliciting an urgent need for effective and highly reliable ...

Towards precision cardiometabolic prevention: results from a machine learning, semi-supervised clustering approach in the nationwide population-based ORISCAV-LUX 2 study.

Given the rapid increase in the incidence of cardiometabolic conditions, there is an urgent need for better approaches to prevent as many cases as pos...

LUNAR :Drug Screening for Novel Coronavirus Based on Representation Learning Graph Convolutional Network.

An outbreak of COVID-19 that began in late 2019 was caused by a novel coronavirus(SARS-CoV-2). It has become a global pandemic. As of June 9, 2020, it...

Deep learning of contagion dynamics on complex networks.

Forecasting the evolution of contagion dynamics is still an open problem to which mechanistic models only offer a partial answer. To remain mathematic...