113 related articles for article (PubMed ID: 21899833)
1. Prediction of acute hypotensive episodes by means of neural network multi-models.
Rocha T; Paredes S; de Carvalho P; Henriques J
Comput Biol Med; 2011 Oct; 41(10):881-90. PubMed ID: 21899833
[TBL] [Abstract][Full Text] [Related]
2. Wavelet based time series forecast with application to acute hypotensive episodes prediction.
Rocha T; Paredes S; Carvalho P; Henriques J; Harris M
Annu Int Conf IEEE Eng Med Biol Soc; 2010; 2010():2403-6. PubMed ID: 21095693
[TBL] [Abstract][Full Text] [Related]
3. A methodology for prediction of acute hypotensive episodes in ICU via a risk scoring model including analysis of ST-segment variations.
Ghaffari A; Homaeinezhad MR; Atarod M; Akraminia M
Cardiovasc Eng; 2010 Mar; 10(1):12-29. PubMed ID: 20054650
[TBL] [Abstract][Full Text] [Related]
4. [Study on predicting model for acute hypotensive episodes in ICU based on support vector machine].
Lai L; Wang Z; Wu X; Xiong D
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 2011 Jun; 28(3):451-5. PubMed ID: 21774200
[TBL] [Abstract][Full Text] [Related]
5. Predicting acute hypotensive episodes based on HR baroreflex model estimation.
Ghaffari A; Jalali A
Cardiovasc Eng; 2009 Dec; 9(4):161-4. PubMed ID: 19830553
[TBL] [Abstract][Full Text] [Related]
6. Parallel processing of ECG and blood pressure waveforms for detection of acute hypotensive episodes: a simulation study using a risk scoring model.
Ghaffari A; Homaeinezhad MR; Atarod M; Akraminia M
Comput Methods Biomech Biomed Engin; 2010; 13(2):197-213. PubMed ID: 19697181
[TBL] [Abstract][Full Text] [Related]
7. Forewarning of hypotensive events using a Bayesian artificial neural network in neurocritical care.
Donald R; Howells T; Piper I; Enblad P; Nilsson P; Chambers I; Gregson B; Citerio G; Kiening K; Neumann J; Ragauskas A; Sahuquillo J; Sinnott R; Stell A;
J Clin Monit Comput; 2019 Feb; 33(1):39-51. PubMed ID: 29799079
[TBL] [Abstract][Full Text] [Related]
8. Prediction of an Acute Hypotensive Episode During an ICU Hospitalization With a Super Learner Machine-Learning Algorithm.
Cherifa M; Blet A; Chambaz A; Gayat E; Resche-Rigon M; Pirracchio R
Anesth Analg; 2020 May; 130(5):1157-1166. PubMed ID: 32287123
[TBL] [Abstract][Full Text] [Related]
9. Rating organ failure via adverse events using data mining in the intensive care unit.
Silva A; Cortez P; Santos MF; Gomes L; Neves J
Artif Intell Med; 2008 Jul; 43(3):179-93. PubMed ID: 18486459
[TBL] [Abstract][Full Text] [Related]
10. Early warning of EUSIG-defined hypotensive events using a Bayesian Artificial Neural Network.
Donald R; Howells T; Piper I; Chambers I; Citerio G; Enblad P; Gregson B; Kiening K; Mattern J; Nilsson P; Ragauskas A; Sahuquillo J; Sinnott R; Stell A
Acta Neurochir Suppl; 2012; 114():39-44. PubMed ID: 22327662
[TBL] [Abstract][Full Text] [Related]
11. [Acute hypotensive episodes prediction based on non-linear chaotic analysis].
Jiang D; Li L; Peng C
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 2015 Feb; 32(1):209-13. PubMed ID: 25997294
[TBL] [Abstract][Full Text] [Related]
12. Predicting Future Occurrence of Acute Hypotensive Episodes Using Noninvasive and Invasive Features.
Sun Y; Rashedi N; Vaze V; Shah P; Halter R; Elliott JT; Paradis NA
Mil Med; 2021 Jan; 186(Suppl 1):445-451. PubMed ID: 33499528
[TBL] [Abstract][Full Text] [Related]
13. Application of generalized dynamic neural networks to biomedical data.
Leistritz L; Galicki M; Kochs E; Zwick EB; Fitzek C; Reichenbach JR; Witte H
IEEE Trans Biomed Eng; 2006 Nov; 53(11):2289-99. PubMed ID: 17073335
[TBL] [Abstract][Full Text] [Related]
14. Reconstruction of physiological signals using iterative retraining and accumulated averaging of neural network models.
McBride J; Sullivan A; Xia H; Petrie A; Zhao X
Physiol Meas; 2011 Jun; 32(6):661-75. PubMed ID: 21566268
[TBL] [Abstract][Full Text] [Related]
15. LDSG-Net: an efficient lightweight convolutional neural network for acute hypotensive episode prediction during ICU hospitalization.
Liu L; Hang Y; Chen R; He X; Jin X; Wu D; Li Y
Physiol Meas; 2024 Jun; 45(6):. PubMed ID: 38772397
[No Abstract] [Full Text] [Related]
16. Prediction of intradialytic hypotension using photoplethysmography.
Solem K; Olde B; Sörnmo L
IEEE Trans Biomed Eng; 2010 Jul; 57(7):1611-9. PubMed ID: 20176537
[TBL] [Abstract][Full Text] [Related]
17. A decision support system to facilitate management of patients with acute gastrointestinal bleeding.
Chu A; Ahn H; Halwan B; Kalmin B; Artifon EL; Barkun A; Lagoudakis MG; Kumar A
Artif Intell Med; 2008 Mar; 42(3):247-59. PubMed ID: 18063351
[TBL] [Abstract][Full Text] [Related]
18. Development of a FPGA based fuzzy neural network system for early diagnosis of critical health condition of a patient.
Chowdhury SR; Saha H
Comput Biol Med; 2010 Feb; 40(2):190-200. PubMed ID: 20070960
[TBL] [Abstract][Full Text] [Related]
19. Artificial neural networks for predicting failure to survive following in-hospital cardiopulmonary resuscitation.
Ebell MH
J Fam Pract; 1993 Mar; 36(3):297-303. PubMed ID: 8454976
[TBL] [Abstract][Full Text] [Related]
20. A dual boundary classifier for predicting acute hypotensive episodes in critical care.
Bhattacharya S; Huddar V; Rajan V; Reddy CK
PLoS One; 2018; 13(2):e0193259. PubMed ID: 29474481
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
