LightGBM-Based Classification of Heart Failure Phenotypes Using Morpho-Energy Features from High-Resolution ECG.
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| Title: | LightGBM-Based Classification of Heart Failure Phenotypes Using Morpho-Energy Features from High-Resolution ECG. |
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| Authors: | Gader MA; Advanced Technologies for Medicine and Signals Laboratory (ATMS), National School of Engineering, University of Sfax, Sfax 3038, Tunisia.; Electrical Engineering Department, National School of Engineering, University of Sfax, Sfax 3038, Tunisia.; Department of Microelectronics & Electronics, Faculty of Polytechnic, University of Mons, 7000 Mons, Belgium., Karmani S; Laboratory of Electronics and Microelectronics (FSM), University of Monastir, Monastir 5000, Tunisia.; Higher Institute of Applied Sciences and Technology of Sousse, University of Sousse, Sousse 4000, Tunisia., Djemal R; Advanced Technologies for Medicine and Signals Laboratory (ATMS), National School of Engineering, University of Sfax, Sfax 3038, Tunisia.; Electrical Engineering Department, National School of Engineering, University of Sfax, Sfax 3038, Tunisia., Sakuyama CV; Department of Microelectronics & Electronics, Faculty of Polytechnic, University of Mons, 7000 Mons, Belgium. |
| Source: | Sensors (Basel, Switzerland) [Sensors (Basel)] 2026 May 27; Vol. 26 (11). Date of Electronic Publication: 2026 May 27. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: MDPI Country of Publication: Switzerland NLM ID: 101204366 Publication Model: Electronic Cited Medium: Internet ISSN: 1424-8220 (Electronic) Linking ISSN: 14248220 NLM ISO Abbreviation: Sensors (Basel) Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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