Cardiac Arrhythmia, Atrial Fibrillation

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Articles published in 2026 in this theme: 9 (scroll down to load remaining articles)

2026

Phone displaying AF High Risk ECG results next to a person applying a wearable heart monitor patch.

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Prediction of Atrial Fibrillation Occurrence With Handheld Mobile Electrocardiogram: Deep Learning Model Development Using Real-World Data

Minje Park, Hyun Jin Ahn, Yeongyeon Na, Sunghoon Joo, Young Ho Lee, Seongwoo Han, Myung Soo Park, Dae Young Cheon, Jeen Hwa Lee, Ki Hong Lee

JMIR Med Inform 2026 (Aug 20); 14:e87142

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Medical professional uses ultrasound device on patient's arm near dialysis machine

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Risk Factors of Arteriovenous Fistula Stenosis in Hemodialysis Patients Using Electronic Stethoscope Monitoring: Prospective Pilot Cohort Study

Wen-Yi Li, Yi-Chen Wu, Bor-Wen Cheng, Feng-Jung Yang

JMIR Form Res 2026 (Aug 18); 10:e97202

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Doctor interacting with futuristic medical display showing brain and heart scans.

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AI-Based Phenotyping of Atrial Fibrillation Through Generative Topographic Mapping: Prospective Murcia Atrial Fibrillation Project III Cohort Study

Eva Soler Espejo, Yang Chen, María Pilar Ramos-Bratos, Sandra Ortega-Martorell, Iván Olier, José Miguel Rivera-Caravaca, Francisco Marín, Vanessa Roldán, Gregory Y.H. Lip

J Med Internet Res 2026 (Aug 06); 28:e90502

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Man in hospital bed with HR vitals monitor showing 76 bpm and accurate heart rate detection.

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A Novel Convolutional Neural Network–Based Algorithm for Heart Rate Measurement From Ballistocardiography Signals in Diverse Clinical Settings: Observational Study

Kumar Chokalingam, Muthukumarasamy Saravanan, Ashish Kaushal, Srishti Rao, Inam Ur Rahman, Ashwathi Nambiar, Mudit Dandwate, Ravi Mahajan, Kunal Sarkar, Gaurav Parchani

JMIR Cardio 2026 (Jul 30); 10:e71224

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2D-CNN model analyzes ECG R-peak data to classify Non-AF, AF, and noise.

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R-R Interval Histogram-Based Deep Learning for 3-Class Atrial Fibrillation Screening in Garment-Type Wearable Holter Electrocardiogram Monitoring: Algorithm Development and Validation Study

Tomoaki Nakano, Keita Okayama, Masanao Yasuoka, Hironori Shigeta, Akito Kawamura, Takayuki Sekihara, Kentaro Ozu, Takafumi Oka, Shigeto Seno, Yasushi Sakata

JMIR Med Inform 2026 (Jul 24); 14:e91960

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Doctor and patient review EKG results on a clipboard.

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Deep Neural Networks for Automatic Atrial Fibrillation Detection Using Long-Term Ambulatory Electrocardiography: Retrospective Diagnostic Accuracy Study

Jagdeep Sedha, Jukka A Lipponen, Antti Aho, Helena Jäntti, Jari Halonen, Tiina M Laitinen, Tomi P Laitinen, Onni E Santala, Mika P Tarvainen, Eemu-Samuli Seljola, Noora S Naukkarinen, Olli Rantula, Tuomas T Rissanen, Juha E K Hartikainen, Tero J Martikainen

JMIR Cardio 2026 (Jun 30); 10:e83714

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Young man at desk holding flyer about sharing voice in health research.

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Experiences of Patients With Atrial Fibrillation Using Technology to Personalize Self-Care Decision-Making: Interpretive Description Study

Kathy L Rush, Cherisse L Seaton, Alexandra Lukey, Victor Wang, Peter S Loewen, Wynne Chiu, Megan Patapoff, Lana Moroz, Jason G Andrade

JMIR Cardio 2026 (Jun 11); 10:e93036

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Medical professionals review ECG data on computer screens, discussing patient care.

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Performance of Vision-Enabled Large Language Models in Image-Based Electrocardiogram Interpretation: Exploratory Evaluation

Nibras Soubh, Eva Rasenack, Helge Haarmann, Felix Wiedmann, Markus Zabel, Constanze Schmidt, Rayan Suliman, Leonard Bergau

J Med Internet Res 2026 (Jun 03); 28:e86692

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Senior man wearing a heart rate monitor chest strap during exercise.

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A Deep Neural Network for Interpreting Wearable Electrocardiogram Data in Atrial Fibrillation: Prospective Observational Diagnostic Accuracy Study

Olli A Rantula, Jukka A Lipponen, Jari Halonen, Helena Jäntti, Onni E Santala, Jagdeep Sedha, Tero J Martikainen, Juha E K Hartikainen, Tuomas T Rissanen, Mika P Tarvainen, Noora S Naukkarinen, Eemu-Samuli Seljola

JMIR Mhealth Uhealth 2026 (Apr 23); 14:e82475

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