AIMC Journal:
BMJ open
Showing 171 to 180 of 213 articles
Artificial intelligence mobile health platform for early detection of COVID-19 in quarantine subjects using a wearable biosensor: protocol for a randomised controlled trial.
BMJ open
Jul 22, 2020
INTRODUCTION: There is an outbreak of COVID-19 worldwide. As there is no effective therapy or vaccine yet, rigorous implementation of traditional public health measures such as isolation and quarantine remains the most effective tool to control the o...
Cloud Computing
Mobile Applications
Respiratory Rate
Randomized Controlled Trials as Topic
Clinical Laboratory Techniques
Quarantine
Betacoronavirus
Coronavirus Infections
Early Diagnosis
Telemedicine
Hong Kong
COVID-19 Testing
Skin Temperature
Heart Rate
Humans
Artificial Intelligence
Pandemics
COVID-19
SARS-CoV-2
Wearable Electronic Devices
Smartphone
Pneumonia, Viral
Blood Gas Monitoring, Transcutaneous
Artificial intelligence method to classify ophthalmic emergency severity based on symptoms: a validation study.
BMJ open
Jul 5, 2020
OBJECTIVES: We investigated the usefulness of machine learning artificial intelligence (AI) in classifying the severity of ophthalmic emergency for timely hospital visits.
Reporting quality of studies using machine learning models for medical diagnosis: a systematic review.
BMJ open
Mar 23, 2020
AIMS: We conducted a systematic review assessing the reporting quality of studies validating models based on machine learning (ML) for clinical diagnosis, with a specific focus on the reporting of information concerning the participants on which the ...
Prediction of caregiver burden in amyotrophic lateral sclerosis: a machine learning approach using random forests applied to a cohort study.
BMJ open
Feb 28, 2020
OBJECTIVES: Amyotrophic lateral sclerosis (ALS) is a rare neurodegenerative disease that is characterised by the rapid degeneration of upper and lower motor neurons and has a fatal trajectory 3-4 years from symptom onset. Due to the nature of the con...
Using a machine learning approach to predict mortality in critically ill influenza patients: a cross-sectional retrospective multicentre study in Taiwan.
BMJ open
Feb 25, 2020
OBJECTIVES: Current mortality prediction models used in the intensive care unit (ICU) have a limited role for specific diseases such as influenza, and we aimed to establish an explainable machine learning (ML) model for predicting mortality in critic...
Development of a system based on artificial intelligence to identify visual problems in children: study protocol of the TrackAI project.
BMJ open
Feb 17, 2020
INTRODUCTION: Around 70% to 80% of the 19 million visually disabled children in the world are due to a preventable or curable disease, if detected early enough. Vision screening in childhood is an evidence-based and cost-effective way to detect visua...
Enablers and barriers to the implementation of socially assistive humanoid robots in health and social care: a systematic review.
BMJ open
Jan 9, 2020
OBJECTIVES: Socially assistive humanoid robots are considered a promising technology to tackle the challenges in health and social care posed by the growth of the ageing population. The purpose of our study was to explore the current evidence on barr...
Characterising and predicting persistent high-cost utilisers in healthcare: a retrospective cohort study in Singapore.
BMJ open
Jan 6, 2020
OBJECTIVE: We aim to characterise persistent high utilisers (PHUs) of healthcare services, and correspondingly, transient high utilisers (THUs) and non-high utilisers (non-HUs) for comparison, to facilitate stratifying HUs for targeted intervention. ...
Current state of science in machine learning methods for automatic infant pain evaluation using facial expression information: study protocol of a systematic review and meta-analysis.
BMJ open
Dec 11, 2019
INTRODUCTION: Infants can experience pain similar to adults, and improperly controlled pain stimuli could have a long-term adverse impact on their cognitive and neurological function development. The biggest challenge of achieving good infant pain co...
Machine learning of physiological waveforms and electronic health record data to predict, diagnose and treat haemodynamic instability in surgical patients: protocol for a retrospective study.
BMJ open
Dec 2, 2019
INTRODUCTION: About 42 million surgeries are performed annually in the USA. While the postoperative mortality is less than 2%, 12% of all patients in the high-risk surgery group account for 80% of postoperative deaths. New onset of haemodynamic insta...
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