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Year | Number of Results |
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2020 | 1 |
2022 | 2 |
2023 | 2 |
2024 | 0 |
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Page 1
Machine Learning-Based Respiration Rate and Blood Oxygen Saturation Estimation Using Photoplethysmogram Signals.
Bioengineering (Basel). 2023 Jan 28;10(2):167. doi: 10.3390/bioengineering10020167.
Bioengineering (Basel). 2023.
PMID: 36829661
Free PMC article.
Lightweight End-to-End Deep Learning Solution for Estimating the Respiration Rate from Photoplethysmogram Signal.
Chowdhury MH, Shuzan MNI, Chowdhury MEH, Reaz MBI, Mahmud S, Al Emadi N, Ayari MA, Ali SHM, Bakar AAA, Rahman SM, Khandakar A.
Chowdhury MH, et al.
Bioengineering (Basel). 2022 Oct 16;9(10):558. doi: 10.3390/bioengineering9100558.
Bioengineering (Basel). 2022.
PMID: 36290527
Free PMC article.
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A Novel Machine Learning Approach for Severity Classification of Diabetic Foot Complications Using Thermogram Images.
Khandakar A, Chowdhury MEH, Reaz MBI, Ali SHM, Kiranyaz S, Rahman T, Chowdhury MH, Ayari MA, Alfkey R, Bakar AAA, Malik RA, Hasan A.
Khandakar A, et al. Among authors: chowdhury mh.
Sensors (Basel). 2022 Jun 2;22(11):4249. doi: 10.3390/s22114249.
Sensors (Basel). 2022.
PMID: 35684870
Free PMC article.
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Self-Attention MHDNet: A Novel Deep Learning Model for the Detection of R-Peaks in the Electrocardiogram Signals Corrupted with Magnetohydrodynamic Effect.
Chowdhury MH, Chowdhury MEH, Khan MS, Ullah MA, Mahmud S, Khandakar A, Hassan A, Tahir AM, Hasan A.
Chowdhury MH, et al.
Bioengineering (Basel). 2023 Apr 28;10(5):542. doi: 10.3390/bioengineering10050542.
Bioengineering (Basel). 2023.
PMID: 37237612
Free PMC article.
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Estimating Blood Pressure from the Photoplethysmogram Signal and Demographic Features Using Machine Learning Techniques.
Chowdhury MH, Shuzan MNI, Chowdhury MEH, Mahbub ZB, Uddin MM, Khandakar A, Reaz MBI.
Chowdhury MH, et al.
Sensors (Basel). 2020 Jun 1;20(11):3127. doi: 10.3390/s20113127.
Sensors (Basel). 2020.
PMID: 32492902
Free PMC article.
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