Cargando…

Machine Learning for Predicting Intubations in Heart Failure Patients: the Challenge of the Right Approach

Detalles Bibliográficos
Autores principales:	Ghanta, Sai Nikhila, Gautam, Nitesh, Mehta, Jawahar L., Al’Aref, Subhi J.
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Springer US 2023
Materias:	Invited Editorial
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9807425/ https://www.ncbi.nlm.nih.gov/pubmed/36593325 http://dx.doi.org/10.1007/s10557-022-07423-y

Ejemplares similares

Artificial Intelligence, Wearables and Remote Monitoring for Heart Failure: Current and Future Applications
por: Gautam, Nitesh, et al.
Publicado: (2022)

A Late Presentation of COVID-19 Vaccine-Induced Myocarditis
por: Gautam, Nitesh, et al.
Publicado: (2021)

Application of deep neural networks for inferring pressure in polymeric acoustic transponders/sensors
por: Alaie, Seyedhamidreza, et al.
Publicado: (2023)

Efficacy and safety of sodium-glucose cotransporter 2 inhibitors initiation in patients with acute heart failure, with and without type 2 diabetes: a systematic review and meta-analysis
por: Salah, Husam M., et al.
Publicado: (2022)

HIGHER HDL CHOLESTEROL LEVELS DECREASE SUSCEPTIBILITY TO COVID-19 INFECTION
por: Chidambaram, Vignesh, et al.
Publicado: (2023)

Utilizing electronic health data and machine learning for the prediction of 30-day unplanned readmission or all-cause mortality in heart failure
por: Beecy, Ashley N., et al.
Publicado: (2020)

Current and Future Applications of Artificial Intelligence in Coronary Artery Disease
por: Gautam, Nitesh, et al.
Publicado: (2022)

Chronic Lymphogranuloma Venereum Proctocolitis Masquerading as Inflammatory Bowel Disease
por: Ghanta, Sai Nikhila, et al.
Publicado: (2022)

Evaluation of Atherosclerotic Plaque in Non-invasive Coronary Imaging
por: Dwivedi, Aeshita, et al.
Publicado: (2018)

Coronary-Cameral Fistula, Thebesian Veins, and Anomalous Coronary Vein on Cardiac Computed Tomography
por: Xu, Jack, et al.
Publicado: (2021)

Severely Calcified Pericardium Causing Constrictive Pericarditis
por: Kaur, Jagdeep, et al.
Publicado: (2023)

Benefit of Heart Rate Reduction in Heart Failure
por: Hasenfuss, Gerd
Publicado: (2010)

Hitting the right target: taxonomic challenges for, and of, plant invasions
por: Pyšek, Petr, et al.
Publicado: (2013)

Mechano-signaling in heart failure
por: Buyandelger, Byambajav, et al.
Publicado: (2014)

The vasculature: a therapeutic target in heart failure?
por: Luxán, Guillermo, et al.
Publicado: (2021)

Epigenetics: a new mechanism of regulation of heart failure?
por: Papait, Roberto, et al.
Publicado: (2013)

Treatment strategies for the right heart in pulmonary hypertension
por: Westerhof, Berend E., et al.
Publicado: (2017)

An augmented reality system for image guidance of transcatheter procedures for structural heart disease
por: Liu, Jun, et al.
Publicado: (2019)

How can we cure a heart “in flame”? A translational view on inflammation in heart failure
por: Hofmann, Ulrich, et al.
Publicado: (2013)

HDL cholesterol levels and susceptibility to COVID-19
por: Chidambaram, Vignesh, et al.
Publicado: (2022)

Determinants of In‐Hospital Mortality After Percutaneous Coronary Intervention: A Machine Learning Approach
por: Al'Aref, Subhi J., et al.
Publicado: (2019)

I -123 metaiodobenzylguanidine imaging for predicting ventricular arrhythmia in heart failure patients
por: Zhou, Weihua, et al.
Publicado: (2013)

Cell therapy in patients with heart failure: a comprehensive review and emerging concepts
por: Bolli, Roberto, et al.
Publicado: (2021)

Inhibition of cardiac CaMKII to cure heart failure: step by step towards translation?
por: Cuello, Friederike, et al.
Publicado: (2016)

The time-to-treatment concept in acute heart failure: Lessons and implications from REALITY-AHF
por: Kagiyama, Nobuyuki, et al.
Publicado: (2018)

Common risk factors for heart failure and cancer
por: Meijers, Wouter C, et al.
Publicado: (2019)

Machine learning‐based prediction of heart failure readmission or death: implications of choosing the right model and the right metrics
por: Awan, Saqib Ejaz, et al.
Publicado: (2019)

Mining multi-center heterogeneous medical data with distributed synthetic learning
por: Chang, Qi, et al.
Publicado: (2023)

Machine Learning Algorithms to Predict Mortality of Neonates on Mechanical Intubation for Respiratory Failure
por: Hsu, Jen-Fu, et al.
Publicado: (2021)

Perspectives by a position statement on atrial fibrillation in acute heart failure a: Mechanisms and therapeutic approaches
por: Okutucu, Sercan, et al.
Publicado: (2020)

Publisher Correction: Mining multi-center heterogeneous medical data with distributed synthetic learning
por: Chang, Qi, et al.
Publicado: (2023)

Inflammatory Cytokines and Chemokines as Therapeutic Targets in Heart Failure
por: Hanna, Anis, et al.
Publicado: (2020)

Beta-blocker therapy in pediatric heart failure: 50 years lost to improve pharmacotherapy of a deadly disease
por: Buchhorn, Reiner
Publicado: (2021)

Failure to Rescue, Failure to Respond
por: Bromberger, Bianca, et al.
Publicado: (2023)

Commentary: Stimulating new options for heart failure management
por: Ryan, Christopher T., et al.
Publicado: (2022)

Getting Costs Right in Global Surgery
por: Shrime, Mark G.
Publicado: (2021)

Must-have Qualities of Clinical Research on Artificial Intelligence and Machine Learning
por: Koçak, Burak, et al.
Publicado: (2023)

Comparing a novel machine learning method to the Friedewald formula and Martin-Hopkins equation for low-density lipoprotein estimation
por: Singh, Gurpreet, et al.
Publicado: (2020)

Scurvy in the Modern World: Extinct or Not?
por: Amisha, FNU, et al.
Publicado: (2022)

End-to-End, Pixel-Wise Vessel-Specific Coronary and Aortic Calcium Detection and Scoring Using Deep Learning
por: Singh, Gurpreet, et al.
Publicado: (2021)

Cannot write session to /tmp/vufind_sessions/sess_t2ntpil9upr8oafuij46cp2epm