Cargando…

Rapid triage for COVID-19 using routine clinical data for patients attending hospital: development and prospective validation of an artificial intelligence screening test

BACKGROUND: The early clinical course of COVID-19 can be difficult to distinguish from other illnesses driving presentation to hospital. However, viral-specific PCR testing has limited sensitivity and results can take up to 72 h for operational reasons. We aimed to develop and validate two early-det...

Descripción completa

Detalles Bibliográficos
Autores principales:	Soltan, Andrew A S, Kouchaki, Samaneh, Zhu, Tingting, Kiyasseh, Dani, Taylor, Thomas, Hussain, Zaamin B, Peto, Tim, Brent, Andrew J, Eyre, David W, Clifton, David A
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	The Author(s). Published by Elsevier Ltd. 2021
Materias:	Articles
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7831998/ https://www.ncbi.nlm.nih.gov/pubmed/33509388 http://dx.doi.org/10.1016/S2589-7500(20)30274-0

Ejemplares similares

Real-world evaluation of rapid and laboratory-free COVID-19 triage for emergency care: external validation and pilot deployment of artificial intelligence driven screening
por: Soltan, Andrew A S, et al.
Publicado: (2022)

A clinical deep learning framework for continually learning from cardiac signals across diseases, time, modalities, and institutions
por: Kiyasseh, Dani, et al.
Publicado: (2021)

Development and validation of early warning score systems for COVID‐19 patients
por: Youssef, Alexey, et al.
Publicado: (2021)

A multi-institutional study using artificial intelligence to provide reliable and fair feedback to surgeons
por: Kiyasseh, Dani, et al.
Publicado: (2023)

The Diagnostic and Triage Accuracy of the GPT-3 Artificial Intelligence Model
por: Levine, David M, et al.
Publicado: (2023)

APPRAISE-HRI: AN ARTIFICIAL INTELLIGENCE ALGORITHM FOR TRIAGE OF HEMORRHAGE CASUALTIES
por: Stallings, Jonathan D., et al.
Publicado: (2023)

Artificial intelligence may enhance emergency triage and management
por: Craca, Michelangelo, et al.
Publicado: (2023)

Algorithmic fairness and bias mitigation for clinical machine learning with deep reinforcement learning
por: Yang, Jenny, et al.
Publicado: (2023)

On the effectiveness of compact biomedical transformers
por: Rohanian, Omid, et al.
Publicado: (2023)

An end-to-end heterogeneous graph attention network for Mycobacterium tuberculosis drug-resistance prediction
por: Yang, Yang, et al.
Publicado: (2021)

Artificial intelligence-based triage of large bowel biopsies can improve workflow
por: Mayall, Frederick George, et al.
Publicado: (2023)

Routine Echocardiography and Artificial Intelligence Solutions
por: Schuuring, Mark J., et al.
Publicado: (2021)

An adversarial training framework for mitigating algorithmic biases in clinical machine learning
por: Yang, Jenny, et al.
Publicado: (2023)

Support Systems of Clinical Decisions in the Triage of the Emergency Department Using Artificial Intelligence: The Efficiency to Support Triage
por: Karlafti, Eleni, et al.
Publicado: (2023)

Predicting scheduled hospital attendance with artificial intelligence
por: Nelson, Amy, et al.
Publicado: (2019)

A Comparison of Artificial Intelligence and Human Doctors for the Purpose of Triage and Diagnosis
por: Baker, Adam, et al.
Publicado: (2020)

Artificial intelligence in medical referrals triage based on Clinical Prioritization Criteria
por: Abdel-Hafez, Ahmad, et al.
Publicado: (2023)

Multi-Label Random Forest Model for Tuberculosis Drug Resistance Classification and Mutation Ranking
por: Kouchaki, Samaneh, et al.
Publicado: (2020)

A data-driven artificial intelligence model for remote triage in the prehospital environment
por: Kim, Dohyun, et al.
Publicado: (2018)

Application of machine learning techniques to tuberculosis drug resistance analysis
por: Kouchaki, Samaneh, et al.
Publicado: (2019)

Emergency department attendance after telephone triage
por: Gibson, Amy, et al.
Publicado: (2017)

Emergency department attendance after telephone triage
por: Denaxas, Spiros, et al.
Publicado: (2017)

Emergency department attendance after telephone triage
por: Ciminata, Giorgio, et al.
Publicado: (2017)

A machine learning and explainable artificial intelligence triage-prediction system for COVID-19
por: Khanna, Varada Vivek, et al.
Publicado: (2023)

Predicting STI Diagnoses Amongst MSM and Young People Attending Sexual Health Clinics in England: Triage Algorithm Development and Validation Using Routine Clinical Data
por: King, Carina, et al.
Publicado: (2018)

Triage of Persons With Tuberculosis Symptoms Using Artificial Intelligence–Based Chest Radiograph Interpretation: A Cost-Effectiveness Analysis
por: Nsengiyumva, Ntwali Placide, et al.
Publicado: (2021)

Artificial Intelligence
por: Karam, P Andrew
Publicado: (2011)

Artificial intelligence in luminal endoscopy
por: Gulati, Shraddha, et al.
Publicado: (2020)

Behavioural artificial intelligence technology for COVID-19 intensivist triage decisions: making the implicit explicit
por: de Metz, Jesse, et al.
Publicado: (2021)

Computer-Aided Pulmonary Fibrosis Detection Leveraging an Advanced Artificial Intelligence Triage and Notification Software
por: Selvan, Kavitha C., et al.
Publicado: (2023)

The quality of vital signs measurements and value preferences in electronic medical records varies by hospital, specialty, and patient demographics
por: Jackson, Niall, et al.
Publicado: (2023)

A signal processing method for alignment-free metagenomic binning: multi-resolution genomic binary patterns
por: Kouchaki, Samaneh, et al.
Publicado: (2019)

Improving patient flow during infectious disease outbreaks using machine learning for real-time prediction of patient readiness for discharge
por: Bishop, Jennifer A., et al.
Publicado: (2021)

An automated COVID-19 triage pipeline using artificial intelligence based on chest radiographs and clinical data
por: Kim, Chris K., et al.
Publicado: (2022)

Triaging self-referred patients attending ophthalmic emergency room
por: AlSamnan, Mazen S., et al.
Publicado: (2015)

Machine learning generalizability across healthcare settings: insights from multi-site COVID-19 screening
por: Yang, Jenny, et al.
Publicado: (2022)

Intelligent Routines
por: Anastassiou, George A, et al.
Publicado: (2013)

Artificial Intelligence-Based Triage for Patients with Acute Abdominal Pain in Emergency Department; a Diagnostic Accuracy Study
por: Farahmand, Shervin, et al.
Publicado: (2017)

THEIA™ development, and testing of artificial intelligence‐based primary triage of diabetic retinopathy screening images in New Zealand
por: Vaghefi, E., et al.
Publicado: (2020)

Artificial Intelligence as a Triage Tool During the Perioperative Period: Pilot Study of Accuracy and Accessibility for Clinical Application
por: Boyd, Carter, et al.
Publicado: (2023)

Cannot write session to /tmp/vufind_sessions/sess_1viqdmcveu5citrqlqbi7tf7bo