Andreas Coppi
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View article: Correction: Computational phenotypes for patients with opioid-related disorders presenting to the emergency department
Correction: Computational phenotypes for patients with opioid-related disorders presenting to the emergency department Open
[This corrects the article DOI: 10.1371/journal.pone.0291572.].
View article: Development and multinational validation of an ensemble deep learning algorithm for detecting and predicting structural heart disease using noisy single-lead electrocardiograms
Development and multinational validation of an ensemble deep learning algorithm for detecting and predicting structural heart disease using noisy single-lead electrocardiograms Open
Aims Artificial intelligence (AI)-enhanced 12-lead electrocardiogram (ECG) can detect a range of structural heart diseases (SHDs); however, it has a limited role in community-based screening. We developed and externally validated a noise-r…
View article: Assessment of health conditions from patient electronic health record portals vs self-reported questionnaires: an analysis of the INSPIRE study
Assessment of health conditions from patient electronic health record portals vs self-reported questionnaires: an analysis of the INSPIRE study Open
Objectives Direct electronic access to multiple electronic health record (EHR) systems through patient portals offers a novel avenue for decentralized research. Given the critical value of patient characterization, we sought to compare com…
View article: Artificial intelligence-guided detection of under-recognised cardiomyopathies on point-of-care cardiac ultrasonography: a multicentre study
Artificial intelligence-guided detection of under-recognised cardiomyopathies on point-of-care cardiac ultrasonography: a multicentre study Open
View article: An Ensemble Deep Learning Algorithm for Structural Heart Disease Screening Using Electrocardiographic Images: PRESENT SHD
An Ensemble Deep Learning Algorithm for Structural Heart Disease Screening Using Electrocardiographic Images: PRESENT SHD Open
Background Identifying structural heart diseases (SHDs) early can change the course of the disease, but their diagnosis requires cardiac imaging, which is limited in accessibility. Objective To leverage images of 12-lead ECGs for automated…
View article: Development and Multinational Validation of an Ensemble Deep Learning Algorithm for Detecting and Predicting Structural Heart Disease Using Noisy Single-lead Electrocardiograms
Development and Multinational Validation of an Ensemble Deep Learning Algorithm for Detecting and Predicting Structural Heart Disease Using Noisy Single-lead Electrocardiograms Open
Background and Aims AI-enhanced 12-lead ECG can detect a range of structural heart diseases (SHDs) but has a limited role in community-based screening. We developed and externally validated a noise-resilient single-lead AI-ECG algorithm th…
View article: Artificial Intelligence–Enhanced Risk Stratification of Cancer Therapeutics–Related Cardiac Dysfunction Using Electrocardiographic Images
Artificial Intelligence–Enhanced Risk Stratification of Cancer Therapeutics–Related Cardiac Dysfunction Using Electrocardiographic Images Open
BACKGROUND: Risk stratification strategies for cancer therapeutics–related cardiac dysfunction (CTRCD) rely on serial monitoring by specialized imaging, limiting their scalability. We aimed to examine an application of artificial intellige…
View article: Tracking the Preclinical Progression of Transthyretin Amyloid Cardiomyopathy Using Artificial Intelligence-Enabled Electrocardiography and Echocardiography
Tracking the Preclinical Progression of Transthyretin Amyloid Cardiomyopathy Using Artificial Intelligence-Enabled Electrocardiography and Echocardiography Open
Background and Aims The diagnosis of transthyretin amyloid cardiomyopathy (ATTR-CM) requires advanced imaging, precluding large-scale pre-clinical testing. Artificial intelligence (AI)-enabled transthoracic echocardiography (TTE) and elect…
View article: The PAX LC Trial: A Decentralized, Phase 2, Randomized, Double-Blind Study of Nirmatrelvir/Ritonavir Compared with Placebo/Ritonavir for Long COVID
The PAX LC Trial: A Decentralized, Phase 2, Randomized, Double-Blind Study of Nirmatrelvir/Ritonavir Compared with Placebo/Ritonavir for Long COVID Open
The PAX LC trial uses a novel decentralized design and a participant-centric approach to test a 15-day regimen of nirmatrelvir/ritonavir for long COVID.
View article: Artificial intelligence-enhanced risk stratification of cancer therapeutics-related cardiac dysfunction using electrocardiographic images
Artificial intelligence-enhanced risk stratification of cancer therapeutics-related cardiac dysfunction using electrocardiographic images Open
Background Risk stratification strategies for cancer therapeutics-related cardiac dysfunction (CTRCD) rely on serial monitoring by specialized imaging, limiting their scalability. Objectives To examine an artificial intelligence (AI)-enhan…
View article: Artificial intelligence-guided detection of under-recognized cardiomyopathies on point-of-care cardiac ultrasound: a multi-center study
Artificial intelligence-guided detection of under-recognized cardiomyopathies on point-of-care cardiac ultrasound: a multi-center study Open
Background Point-of-care ultrasonography (POCUS) enables cardiac imaging at the bedside and in communities but is limited by abbreviated protocols and variation in quality. We developed and tested artificial intelligence (AI) models to aut…
View article: Artificial Intelligence-Based Automated Interpretation of Images of Electrocardiograms: Development and Multinational Validation of ECG-GPT
Artificial Intelligence-Based Automated Interpretation of Images of Electrocardiograms: Development and Multinational Validation of ECG-GPT Open
Background Timely and accurate assessment of electrocardiograms (ECGs) is crucial for diagnosing, triaging, and clinically managing patients. Current workflows rely on computerized ECG interpretation tools built into ECG signal acquisition…
View article: A Multimodality Video-Based AI Biomarker For Aortic Stenosis Development And Progression
A Multimodality Video-Based AI Biomarker For Aortic Stenosis Development And Progression Open
Importance Aortic stenosis (AS) is a major public health challenge with a growing therapeutic landscape, but current biomarkers do not inform personalized screening and follow-up. Objective A video-based artificial intelligence (AI) biomar…
View article: Computational phenotypes for patients with opioid-related disorders presenting to the emergency department
Computational phenotypes for patients with opioid-related disorders presenting to the emergency department Open
Objective We aimed to discover computationally-derived phenotypes of opioid-related patient presentations to the ED via clinical notes and structured electronic health record (EHR) data. Methods This was a retrospective study of ED visits …
View article: Automated Identification of Heart Failure with Reduced Ejection Fraction using Deep Learning-based Natural Language Processing
Automated Identification of Heart Failure with Reduced Ejection Fraction using Deep Learning-based Natural Language Processing Open
Background The lack of automated tools for measuring care quality has limited the implementation of a national program to assess and improve guideline-directed care in heart failure with reduced ejection fraction (HFrEF). A key challenge f…
View article: An AI-powered patient triage platform for future viral outbreaks using COVID-19 as a disease model
An AI-powered patient triage platform for future viral outbreaks using COVID-19 as a disease model Open
View article: Severe aortic stenosis detection by deep learning applied to echocardiography
Severe aortic stenosis detection by deep learning applied to echocardiography Open
Background and Aims Early diagnosis of aortic stenosis (AS) is critical to prevent morbidity and mortality but requires skilled examination with Doppler imaging. This study reports the development and validation of a novel deep learning mo…
View article: Detection of left ventricular systolic dysfunction from single-lead electrocardiography adapted for portable and wearable devices
Detection of left ventricular systolic dysfunction from single-lead electrocardiography adapted for portable and wearable devices Open
View article: Evaluation of Plasma Biomarkers to Predict Major Adverse Kidney Events in Hospitalized Patients With COVID-19
Evaluation of Plasma Biomarkers to Predict Major Adverse Kidney Events in Hospitalized Patients With COVID-19 Open
View article: Computational Phenotypes for Patients with Opioid-Related Disorders Presenting to the Emergency Department
Computational Phenotypes for Patients with Opioid-Related Disorders Presenting to the Emergency Department Open
Objective We aimed to discover computationally-derived phenotypes of opioid-related patient presentations to the emergency department (ED) via clinical notes and structured electronic health record (EHR) data. Methods This was a retrospect…
View article: Detection of Left Ventricular Systolic Dysfunction from Single-Lead Electrocardiography Adapted for Wearable Devices
Detection of Left Ventricular Systolic Dysfunction from Single-Lead Electrocardiography Adapted for Wearable Devices Open
Artificial intelligence (AI) can detect left ventricular systolic dysfunction (LVSD) from electrocardiograms (ECGs). Wearable devices could allow for broad AI-based screening but frequently obtain noisy ECGs. We report a novel strategy tha…
View article: Association between primary or booster COVID-19 mRNA vaccination and Omicron lineage BA.1 SARS-CoV-2 infection in people with a prior SARS-CoV-2 infection: A test-negative case–control analysis
Association between primary or booster COVID-19 mRNA vaccination and Omicron lineage BA.1 SARS-CoV-2 infection in people with a prior SARS-CoV-2 infection: A test-negative case–control analysis Open
Background The benefit of primary and booster vaccination in people who experienced a prior Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection remains unclear. The objective of this study was to estimate the effectivene…
View article: Use of Whole-Genome Sequencing to Estimate the Contribution of Immune Evasion and Waning Immunity on Decreasing COVID-19 Vaccine Effectiveness
Use of Whole-Genome Sequencing to Estimate the Contribution of Immune Evasion and Waning Immunity on Decreasing COVID-19 Vaccine Effectiveness Open
Background The impact variant-specific immune evasion and waning protection have on declining coronavirus disease 2019 (COVID-19) vaccine effectiveness (VE) remains unclear. Using whole-genome sequencing (WGS), we examined the contribution…
View article: Automated severe aortic stenosis detection on single-view echocardiography: A multi-center deep learning study
Automated severe aortic stenosis detection on single-view echocardiography: A multi-center deep learning study Open
Background and Aims Early diagnosis of aortic stenosis (AS) is critical to prevent morbidity and mortality but requires skilled examination with Doppler imaging. This study reports the development and validation of a novel deep learning mo…
View article: Use of whole genome sequencing to estimate the contribution of immune evasion and waning immunity to decreasing COVID-19 vaccine effectiveness during alpha and delta variant waves
Use of whole genome sequencing to estimate the contribution of immune evasion and waning immunity to decreasing COVID-19 vaccine effectiveness during alpha and delta variant waves Open
Background The decline in COVID-19 mRNA vaccine effectiveness (VE) is well established, however the impact of variant-specific immune evasion and waning protection remains unclear. Here, we use whole-genome-sequencing (WGS) to tease apart …
View article: Effectiveness of Primary and Booster COVID-19 mRNA Vaccination against Omicron Variant SARS-CoV-2 Infection in People with a Prior SARS-CoV-2 Infection
Effectiveness of Primary and Booster COVID-19 mRNA Vaccination against Omicron Variant SARS-CoV-2 Infection in People with a Prior SARS-CoV-2 Infection Open
Background The benefit of vaccination in people who experienced a prior SARS-CoV-2 infection remains unclear. Objective To estimate the effectiveness of primary (two-dose) and booster (third dose) vaccination against Omicron infection amon…
View article: Rapid emergence of SARS-CoV-2 Omicron variant is associated with an infection advantage over Delta in vaccinated persons
Rapid emergence of SARS-CoV-2 Omicron variant is associated with an infection advantage over Delta in vaccinated persons Open
View article: Rapid emergence of SARS-CoV-2 Omicron variant is associated with an infection advantage over Delta in vaccinated persons
Rapid emergence of SARS-CoV-2 Omicron variant is associated with an infection advantage over Delta in vaccinated persons Open
The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants continues to shape the coronavirus disease 2019 (Covid-19) pandemic. The detection and rapid spread of the SARS-CoV-2 ‘ Omicron’ variant (lineage B.1.1.…
View article: Comparison of infectious SARS-CoV-2 from the nasopharynx of vaccinated and unvaccinated individuals
Comparison of infectious SARS-CoV-2 from the nasopharynx of vaccinated and unvaccinated individuals Open
The frequency of SARS-CoV-2 breakthrough infections in fully vaccinated individuals increased with the emergence of the Delta variant, particularly with longer time from vaccine completion. However, whether breakthrough infections lead to …
View article: Prognostic Significance of Urinary Biomarkers in Patients Hospitalized With COVID-19
Prognostic Significance of Urinary Biomarkers in Patients Hospitalized With COVID-19 Open