These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

154 related articles for article (PubMed ID: 36650798)

  • 21. An affordable cuff-less blood pressure estimation solution.
    Jain M; Kumar N; Deb S
    Annu Int Conf IEEE Eng Med Biol Soc; 2016 Aug; 2016():5294-5297. PubMed ID: 28325023
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Non-Invasive Continuous Blood-Pressure Monitoring Models Based on Photoplethysmography and Electrocardiography.
    Wu H; Ji Z; Li M
    Sensors (Basel); 2019 Dec; 19(24):. PubMed ID: 31847474
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Real-Time Cuffless Continuous Blood Pressure Estimation Using 1D Squeeze U-Net Model: A Progress toward mHealth.
    Athaya T; Choi S
    Biosensors (Basel); 2022 Aug; 12(8):. PubMed ID: 36005051
    [TBL] [Abstract][Full Text] [Related]  

  • 24. An Adaptive Weight Learning-Based Multitask Deep Network for Continuous Blood Pressure Estimation Using Electrocardiogram Signals.
    Fan X; Wang H; Zhao Y; Li Y; Tsui KL
    Sensors (Basel); 2021 Feb; 21(5):. PubMed ID: 33668778
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Non-invasive cuff-less blood pressure machine learning algorithm using photoplethysmography and prior physiological data.
    Yang S; Morgan SP; Cho SY; Correia R; Wen L; Zhang Y
    Blood Press Monit; 2021 Aug; 26(4):312-320. PubMed ID: 33741776
    [TBL] [Abstract][Full Text] [Related]  

  • 26. SVR ensemble-based continuous blood pressure prediction using multi-channel photoplethysmogram.
    Kei Fong MW; Ng EYK; Er Zi Jian K; Hong TJ
    Comput Biol Med; 2019 Oct; 113():103392. PubMed ID: 31446317
    [TBL] [Abstract][Full Text] [Related]  

  • 27. A Refined Blood Pressure Estimation Model Based on Single Channel Photoplethysmography.
    Zhang Y; Ren X; Liang X; Ye X; Zhou C
    IEEE J Biomed Health Inform; 2022 Dec; 26(12):5907-5917. PubMed ID: 36103444
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Machine Learning Approaches For Improved Continuous, Non-occlusive Arterial Pressure Monitoring Using Photoplethysmography.
    Jorge J; Proenca M; Aguet C; Van Zaen J; Bonnier G; Renevey P; Lemkaddem A; Schoettker P; Lemay M
    Annu Int Conf IEEE Eng Med Biol Soc; 2020 Jul; 2020():910-913. PubMed ID: 33018132
    [TBL] [Abstract][Full Text] [Related]  

  • 29. 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
    Sensors (Basel); 2020 Jun; 20(11):. PubMed ID: 32492902
    [TBL] [Abstract][Full Text] [Related]  

  • 30. A Comparison of Wearable Tonometry, Photoplethysmography, and Electrocardiography for Cuffless Measurement of Blood Pressure in an Ambulatory Setting.
    Mieloszyk R; Twede H; Lester J; Wander J; Basu S; Cohn G; Smith G; Morris D; Gupta S; Tan D; Villar N; Wolf M; Malladi S; Mickelson M; Ryan L; Kim L; Kepple J; Kirchner S; Wampler E; Terada R; Robinson J; Paulsen R; Saponas TS
    IEEE J Biomed Health Inform; 2022 Jul; 26(7):2864-2875. PubMed ID: 35201992
    [TBL] [Abstract][Full Text] [Related]  

  • 31. A novel method for continuous blood pressure estimation based on a single-channel photoplethysmogram signal.
    Hu Q; Deng X; Wang A; Yang C
    Physiol Meas; 2021 Jan; 41(12):125009. PubMed ID: 33166940
    [TBL] [Abstract][Full Text] [Related]  

  • 32. A Shallow U-Net Architecture for Reliably Predicting Blood Pressure (BP) from Photoplethysmogram (PPG) and Electrocardiogram (ECG) Signals.
    Mahmud S; Ibtehaz N; Khandakar A; Tahir AM; Rahman T; Islam KR; Hossain MS; Rahman MS; Musharavati F; Ayari MA; Islam MT; Chowdhury MEH
    Sensors (Basel); 2022 Jan; 22(3):. PubMed ID: 35161664
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Cuffless and Continuous Blood Pressure Estimation From PPG Signals Using Recurrent Neural Networks.
    El Hajj C; Kyriacou PA
    Annu Int Conf IEEE Eng Med Biol Soc; 2020 Jul; 2020():4269-4272. PubMed ID: 33018939
    [TBL] [Abstract][Full Text] [Related]  

  • 34. A Non-Invasive Continuous Blood Pressure Estimation Approach Based on Machine Learning.
    Chen S; Ji Z; Wu H; Xu Y
    Sensors (Basel); 2019 Jun; 19(11):. PubMed ID: 31174357
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Estimating Systolic Blood Pressure Using Convolutional Neural Networks.
    Rastegar S; Gholamhosseini H; Lowe A; Mehdipour F; Lindén M
    Stud Health Technol Inform; 2019; 261():143-149. PubMed ID: 31156106
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Generalization Error of a Regression Model for Non-Invasive Blood Pressure Monitoring using a Single Photoplethysmography (PPG) Signal.
    Zylinski M; Occhipinti E; Mandic D
    Annu Int Conf IEEE Eng Med Biol Soc; 2023 Jul; 2023():i-iv. PubMed ID: 38083115
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Blood Pressure Estimation from Photoplethysmogram Using a Spectro-Temporal Deep Neural Network.
    Slapničar G; Mlakar N; Luštrek M
    Sensors (Basel); 2019 Aug; 19(15):. PubMed ID: 31382703
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Personalized Blood Pressure Estimation Using Photoplethysmography: A Transfer Learning Approach.
    Leitner J; Chiang PH; Dey S
    IEEE J Biomed Health Inform; 2022 Jan; 26(1):218-228. PubMed ID: 34077378
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Continuous blood pressure prediction system using Conv-LSTM network on hybrid latent features of photoplethysmogram (PPG) and electrocardiogram (ECG) signals.
    Kamanditya B; Fuadah YN; Mahardika T NQ; Lim KM
    Sci Rep; 2024 Jul; 14(1):16450. PubMed ID: 39014018
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Non-Invasive Blood Pressure Sensing via Machine Learning.
    Attivissimo F; D'Alessandro VI; De Palma L; Lanzolla AML; Di Nisio A
    Sensors (Basel); 2023 Oct; 23(19):. PubMed ID: 37837172
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 8.