Application of Artificial Intelligence and Machine Learning in Arrhythmia Detection and Pacemaker Data Analysis
Lu Huan Shen, Ke Qiang Xu, Peng Fei Xia, Jian Chen · 2026
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Description
Lu Huan Shen, Ke Qiang Xu, Peng Fei Xia, and Jian Chen reviewed AI and machine learning in two thousand twenty-six for finding rhythm disorders and mining pacemaker data. Computing power and smarter algorithms have pushed these tools deep into heart medicine. Their review traces the path from classic machine learning to deep learning in both areas.
They weigh gains in diagnosis accuracy, outcome prediction, and treatment planning. Real-world use inside major commercial ECG reading systems is covered, as is fresh work on pacemaker spike signals that standard detectors often miss. Hurdles remain in data standards, model clarity, and outside validation, but the authors see a central future role.
Catalog record
| CREATOR | Lu Huan Shen, Ke Qiang Xu, Peng Fei Xia, Jian Chen |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 35 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |