Surveillance

Artificial intelligence mobile health platform for early detection of COVID-19 in quarantine subjects using a wearable biosensor: protocol for a randomised controlled trial.

INTRODUCTION: There is an outbreak of COVID-19 worldwide. As there is no effective therapy or vaccin...

Challenges of machine learning model validation using correlated behaviour data: Evaluation of cross-validation strategies and accuracy measures.

Automated monitoring of the movements and behaviour of animals is a valuable research tool. Recently...

Data Augmentation and Pretraining for Template-Based Retrosynthetic Prediction in Computer-Aided Synthesis Planning.

This work presents efforts to augment the performance of data-driven machine learning algorithms for...

An Artificial Intelligence Model for Predicting 1-Year Survival of Bone Metastases in Non-Small-Cell Lung Cancer Patients Based on XGBoost Algorithm.

Non-small-cell lung cancer (NSCLC) patients often develop bone metastases (BM), and the overall surv...

What is the optimal surveillance strategy for non-dysplastic Barrett's esophagus?

PURPOSE OF REVIEW: There is conflicting data on the effectiveness of the currently recommended endos...

Artificial intelligence-based tools to control healthcare associated infections: A systematic review of the literature.

BACKGROUND: Healthcare-associated infections (HAIs) are the most frequent adverse events in healthca...

A systematic review of machine learning models for predicting outcomes of stroke with structured data.

BACKGROUND AND PURPOSE: Machine learning (ML) has attracted much attention with the hope that it cou...

3D-Convolutional Neural Network with Generative Adversarial Network and Autoencoder for Robust Anomaly Detection in Video Surveillance.

As the surveillance devices proliferate, various machine learning approaches for video anomaly detec...

Deep learning for predicting the occurrence of cardiopulmonary diseases in Nanjing, China.

The efficiency of disease prevention and medical care service necessitated the prediction of inciden...

Forecasting tuberculosis using diabetes-related google trends data.

Online activity-based data can be used to aid infectious disease forecasting. Our aim was to exploit...

Forecasting and Evaluating Multiple Interventions for COVID-19 Worldwide.

As the Covid-19 pandemic surges around the world, questions arise about the number of global cases a...

Deep learning in generating radiology reports: A survey.

Substantial progress has been made towards implementing automated radiology reporting models based o...

Ethics and governance for digital disease surveillance.

Knowledge Graph-Enabled Cancer Data Analytics.

Cancer registries collect unstructured and structured cancer data for surveillance purposes which pr...

How Big Data and Artificial Intelligence Can Help Better Manage the COVID-19 Pandemic.

SARS-CoV2 is a novel coronavirus, responsible for the COVID-19 pandemic declared by the World Health...

Towards a fully automated surveillance of well-being status in laboratory mice using deep learning: Starting with facial expression analysis.

Assessing the well-being of an animal is hindered by the limitations of efficient communication betw...

How Artificial Intelligence Will Impact Colonoscopy and Colorectal Screening.

Artificial intelligence may improve value in colonoscopy-based colorectal screening and surveillance...

Flaws (and quality) in research today: can artificial intelligence intervene?

The existing flaws in both conducting and reporting of research have been outlined and criticized in...

Artificial Intelligence in Dermatology: A Primer.

Artificial intelligence is becoming increasingly important in dermatology, with studies reporting ac...

Artificial intelligence versus clinicians: systematic review of design, reporting standards, and claims of deep learning studies.

OBJECTIVE: To systematically examine the design, reporting standards, risk of bias, and claims of st...

Reporting quality of studies using machine learning models for medical diagnosis: a systematic review.

AIMS: We conducted a systematic review assessing the reporting quality of studies validating models ...