Public Health & Policy

Measuring Patient Similarity on Multiple Diseases by Joint Learning via a Convolutional Neural Network.

Patient similarity research is one of the most fundamental tasks in healthcare, helping to make decisions without incurring additional time and costs in clinical practices. Patient similarity can also apply to various medical fields, such as cohort analysis and personalized treatment recommendations. Because of this importance, patient similarity measurement studies are actively being conducted. H...

Sacubitril/valsartan reduces indications for arrhythmic primary prevention in heart failure with reduced ejection fraction: insights from DISCOVER-ARNI, a multicenter Italian register.

AIMS: This sub-study deriving from a multicentre Italian register [Deformation Imaging by Strain in Chronic Heart Failure Over Sacubitril-Valsartan: A Multicenter Echocardiographic Registry (DISCOVER)-ARNI] investigated whether sacubitril/valsartan in addition to optimal medical therapy (OMT) could reduce the rate of implantable cardioverter-defibrillator (ICD) indications for primary prevention i...

LightAnomalyNet: A Lightweight Framework for Efficient Abnormal Behavior Detection.

The continuous development of intelligent video surveillance systems has increased the demand for enhanced vision-based methods of automated detection...

Traceable impedance-based single-cell pipetting, from a research set-up to a robust and fast automated robot: DispenCell-S1.

Single-cell isolation is a truly transformative tool for the understanding of biological systems. It allows single-cell molecular analyses and conside...

Crop loss identification at field parcel scale using satellite remote sensing and machine learning.

Identifying crop loss at field parcel scale using satellite images is challenging: first, crop loss is caused by many factors during the growing seaso...

D2-CovidNet: A Deep Learning Model for COVID-19 Detection in Chest X-Ray Images.

Since the outbreak of Coronavirus disease 2019 (COVID-19), it has been spreading rapidly worldwide and has not yet been effectively controlled. Many r...

The COVID-19 epidemic analysis and diagnosis using deep learning: A systematic literature review and future directions.

Since December 2019, the COVID-19 outbreak has resulted in countless deaths and has harmed all facets of human existence. COVID-19 has been designated...

A computer-aided diagnosis system for the classification of COVID-19 and non-COVID-19 pneumonia on chest X-ray images by integrating CNN with sparse autoencoder and feed forward neural network.

Several infectious diseases have affected the lives of many people and have caused great dilemmas all over the world. COVID-19 was declared a pandemic...

Lung detection and severity prediction of pneumonia patients based on COVID-19 DET-PRE network.

BACKGROUND: The sudden outbreak of COVID-19 pneumonia has brought a heavy disaster to individuals globally. Facing this new virus, the clinicians have...

Population Preferences for Performance and Explainability of Artificial Intelligence in Health Care: Choice-Based Conjoint Survey.

BACKGROUND: Certain types of artificial intelligence (AI), that is, deep learning models, can outperform health care professionals in particular domai...

Trustworthy AI: Closing the gap between development and integration of AI systems in ophthalmic practice.

An increasing number of artificial intelligence (AI) systems are being proposed in ophthalmology, motivated by the variety and amount of clinical and ...

Face mask recognition system using CNN model.

COVID-19 epidemic has swiftly disrupted our day-to-day lives affecting the international trade and movements. Wearing a face mask to protect one's fac...

Water tank and swimming pool detection based on remote sensing and deep learning: Relationship with socioeconomic level and applications in dengue control.

Studies have shown that areas with lower socioeconomic standings are often more vulnerable to dengue and similar deadly diseases that can be spread th...

xViTCOS: Explainable Vision Transformer Based COVID-19 Screening Using Radiography.

Since its outbreak, the rapid spread of COrona VIrus Disease 2019 (COVID-19) across the globe has pushed the health care system in many countries to ...

Deep Learning Enables Accurate Diagnosis of Novel Coronavirus (COVID-19) With CT Images.

A novel coronavirus (COVID-19) recently emerged as an acute respiratory syndrome, and has caused a pneumonia outbreak world-widely. As the COVID-19 co...

A Deep Learning Framework Integrating the Spectral and Spatial Features for Image-Assisted Medical Diagnostics.

The development of a computer-aided disease detection system to ease the long and arduous manual diagnostic process is an emerging research interest. ...

Comparison of Machine Learning Techniques for Mortality Prediction in a Prospective Cohort of Older Adults.

As global demographics change, ageing is a global phenomenon which is increasingly of interest in our modern and rapidly changing society. Thus, the a...

A weakly supervised model for the automated detection of adverse events using clinical notes.

With clinical trials unable to detect all potential adverse reactions to drugs and medical devices prior to their release into the market, accurate po...

Knowledge graph analysis and visualization of AI technology applied in COVID-19.

With the global outbreak of coronavirus disease (COVID-19) all over the world, artificial intelligence (AI) technology is widely used in COVID-19 and ...

AI in predicting COPD in the Canadian population.

Chronic obstructive pulmonary disease (COPD) is a progressive lung disease that produces non-reversible airflow limitations. Approximately 10% of Cana...