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A new method of modeling the multi-stage decision-making process of CRT using machine learning with uncertainty quantification

Autor: Larsen, Kristoffer, Zhao, Chen, Keyak, Joyce, Sha, Qiuying, Paez, Diana, Zhang, Xinwei, Hung, Guang-Uei, Zou, Jiangang, Peix, Amalia, Zhou, Weihua

Aims. The purpose of this study is to create a multi-stage machine learning model to predict cardiac resynchronization therapy (CRT) response for heart failure (HF) patients. This model exploits uncertainty quantification to recommend additional coll

Externí odkaz: http://arxiv.org/abs/2309.08415

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A Framework for Identifying Depression on Social Media: MentalRiskES@IberLEF 2023

Autor: Viloria, Simon Sanchez, del Río, Daniel Peix, Cabo, Rubén Bermúdez, Fuentes, Guillermo Arturo Arrojo, Segura-Bedmar, Isabel

This paper describes our participation in the MentalRiskES task at IberLEF 2023. The task involved predicting the likelihood of an individual experiencing depression based on their social media activity. The dataset consisted of conversations from 17

Externí odkaz: http://arxiv.org/abs/2306.16125

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A new method using deep learning to predict the response to cardiac resynchronization therapy

Autor: Larsena, Kristoffer, He, Zhuo, Zhao, Chen, Zhang, Xinwei, Sha, Quiying, Mesquitad, Claudio T, Paeze, Diana, Garciaf, Ernest V., Zou, Jiangang, Peix, Amalia, Zhou, Weihua

Background. Clinical parameters measured from gated single-photon emission computed tomography myocardial perfusion imaging (SPECT MPI) have value in predicting cardiac resynchronization therapy (CRT) patient outcomes, but still show limitations. The

Externí odkaz: http://arxiv.org/abs/2305.02475

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A new method using machine learning to integrate ECG and gated SPECT MPI for Cardiac Resynchronization Therapy Decision Support on behalf of the VISION-CRT

Autor: Fernandes, Fernando de A., Larsen, Kristoffer, He, Zhuo, Nascimento, Erivelton, Peix, Amalia, Sha, Qiuying, Paez, Diana, Garcia, Ernest V., Zhou, Weihua, Mesquita, Claudio T

Cardiac resynchronization therapy (CRT) has been established as an important therapy for heart failure. Mechanical dyssynchrony has the potential to predict responders to CRT. The aim of this study was to report the development and the validation of

Externí odkaz: http://arxiv.org/abs/2211.07472

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