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Emese Sükei

Showing results (1-10 of 8) with videos related to

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Internet Interventions|August 23, 2023
Automatic patient functionality assessment from multimodal data using deep learning techniques - Development and feasibility evaluationEmese Sükei, Santiago de Leon-Martinez, Pablo M Olmos, et al.
JMIR Mhealth and Uhealth|March 22, 2021
Predicting Emotional States Using Behavioral Markers Derived From Passively Sensed Data: Data-Driven Machine Learning ApproachEmese Sükei, Agnes Norbury, M Mercedes Perez-Rodriguez, et al.
Bioinformatics (Oxford, England)|November 24, 2023
Multimodal learning in clinical proteomics: enhancing antimicrobial resistance prediction models with chemical informationGiovanni Visonà, Diane Duroux, Lucas Miranda, et al.
Scientific Reports|November 5, 2024
Multi-modal representation learning in retinal imaging using self-supervised learning for enhanced clinical predictionsEmese Sükei, Elisabeth Rumetshofer, Niklas Schmidinger, et al.
NPJ Digital Medicine|September 25, 2025
Multimodal foundation model and benchmark for comprehensive retinal OCT image analysisJosé Morano, Botond Fazekas, Emese Sükei, et al.
JMIR Mental Health|September 15, 2021
Shift in Social Media App Usage During COVID-19 Lockdown and Clinical Anxiety Symptoms: Machine Learning-Based Ecological Momentary Assessment StudyJihan Ryu, Emese Sükei, Agnes Norbury, et al.
JMIR Formative Research|October 30, 2023
Continuous Assessment of Function and Disability via Mobile Sensing: Real-World Data-Driven Feasibility StudyEmese Sükei, Lorena Romero-Medrano, Santiago de Leon-Martinez, et al.
Scientific Reports|February 17, 2026
Artificial Intelligence-based characterization of therapeutic response in fluid types and volumes influencing retinal function in neovascular age-related macular degenerationSophie Frank-Publig, Wolf Buehl, Virginia Mares, et al.
Pageof 1

Showing results (1-10 of 8) with videos related to

Sort By:
Pageof 1
Internet Interventions|August 23, 2023
Automatic patient functionality assessment from multimodal data using deep learning techniques - Development and feasibility evaluationEmese Sükei, Santiago de Leon-Martinez, Pablo M Olmos, et al.
JMIR Mhealth and Uhealth|March 22, 2021
Predicting Emotional States Using Behavioral Markers Derived From Passively Sensed Data: Data-Driven Machine Learning ApproachEmese Sükei, Agnes Norbury, M Mercedes Perez-Rodriguez, et al.
Bioinformatics (Oxford, England)|November 24, 2023
Multimodal learning in clinical proteomics: enhancing antimicrobial resistance prediction models with chemical informationGiovanni Visonà, Diane Duroux, Lucas Miranda, et al.
Scientific Reports|November 5, 2024
Multi-modal representation learning in retinal imaging using self-supervised learning for enhanced clinical predictionsEmese Sükei, Elisabeth Rumetshofer, Niklas Schmidinger, et al.
NPJ Digital Medicine|September 25, 2025
Multimodal foundation model and benchmark for comprehensive retinal OCT image analysisJosé Morano, Botond Fazekas, Emese Sükei, et al.
JMIR Mental Health|September 15, 2021
Shift in Social Media App Usage During COVID-19 Lockdown and Clinical Anxiety Symptoms: Machine Learning-Based Ecological Momentary Assessment StudyJihan Ryu, Emese Sükei, Agnes Norbury, et al.
JMIR Formative Research|October 30, 2023
Continuous Assessment of Function and Disability via Mobile Sensing: Real-World Data-Driven Feasibility StudyEmese Sükei, Lorena Romero-Medrano, Santiago de Leon-Martinez, et al.
Scientific Reports|February 17, 2026
Artificial Intelligence-based characterization of therapeutic response in fluid types and volumes influencing retinal function in neovascular age-related macular degenerationSophie Frank-Publig, Wolf Buehl, Virginia Mares, et al.
Pageof 1