115 related articles for article (PubMed ID: 38772397)
1. 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]
2. 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]
3. 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]
4. A machine learning method for acute hypotensive episodes prediction using only non-invasive parameters.
Zhang G; Yuan J; Yu M; Wu T; Luo X; Chen F
Comput Methods Programs Biomed; 2021 Mar; 200():105845. PubMed ID: 33309303
[TBL] [Abstract][Full Text] [Related]
5. SDS-Net: A lightweight 3D convolutional neural network with multi-branch attention for multimodal brain tumor accurate segmentation.
Wu Q; Pei Y; Cheng Z; Hu X; Wang C
Math Biosci Eng; 2023 Sep; 20(9):17384-17406. PubMed ID: 37920059
[TBL] [Abstract][Full Text] [Related]
6. 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]
7. 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]
8. The Role of Baroreflex Sensitivity in Acute Hypotensive Episodes Prediction in the Intensive Care Unit.
Angelotti G; Morandini P; Lehman LH; Mark RG; Barbieri R
Annu Int Conf IEEE Eng Med Biol Soc; 2018 Jul; 2018():2784-2787. PubMed ID: 30440979
[TBL] [Abstract][Full Text] [Related]
9. Prediction of Patient-specific Acute Hypotensive Episodes in ICU Using Deep Models.
Chan B; Sedghi A; Laird P; Maslove D; Mousavi P
Annu Int Conf IEEE Eng Med Biol Soc; 2019 Jul; 2019():566-569. PubMed ID: 31945962
[TBL] [Abstract][Full Text] [Related]
10. [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]
11. 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]
12. An extremely lightweight CNN model for the diagnosis of chest radiographs in resource-constrained environments.
Kumar G; Sharma N; Paul A
Med Phys; 2023 Dec; 50(12):7568-7578. PubMed ID: 37665774
[TBL] [Abstract][Full Text] [Related]
13. [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]
14. EEG-CDILNet: a lightweight and accurate CNN network using circular dilated convolution for motor imagery classification.
Liang T; Yu X; Liu X; Wang H; Liu X; Dong B
J Neural Eng; 2023 Aug; 20(4):. PubMed ID: 37552978
[No Abstract] [Full Text] [Related]
15. Hypotension Risk Prediction via Sequential Contrast Patterns of ICU Blood Pressure.
Ghosh S; Feng M; Nguyen H; Li J
IEEE J Biomed Health Inform; 2016 Sep; 20(5):1416-1426. PubMed ID: 26168449
[TBL] [Abstract][Full Text] [Related]
16. CeLNet: a correlation-enhanced lightweight network for medical image segmentation.
Zhang B; Wang X; Liu L; Zhang D; Huang X; Xia M; Jiang W; Huang X
Phys Med Biol; 2023 May; 68(11):. PubMed ID: 37172613
[No Abstract] [Full Text] [Related]
17. Attention-aided lightweight networks friendly to smart weeding robot hardware resources for crops and weeds semantic segmentation.
Wei Y; Feng Y; Zhou X; Wang G
Front Plant Sci; 2023; 14():1320448. PubMed ID: 38186601
[TBL] [Abstract][Full Text] [Related]
18. Generalizable deep temporal models for predicting episodes of sudden hypotension in critically ill patients: a personalized approach.
Chan B; Chen B; Sedghi A; Laird P; Maslove D; Mousavi P
Sci Rep; 2020 Jul; 10(1):11480. PubMed ID: 32651401
[TBL] [Abstract][Full Text] [Related]
19. A machine-learning approach to predicting hypotensive events in ICU settings.
Moghadam MC; Abad EMK; Bagherzadeh N; Ramsingh D; Li GP; Kain ZN
Comput Biol Med; 2020 Mar; 118():103626. PubMed ID: 32174328
[TBL] [Abstract][Full Text] [Related]
20. Exploring convolutional neural networks with transfer learning for diagnosing Lyme disease from skin lesion images.
Hossain SI; de Goër de Herve J; Hassan MS; Martineau D; Petrosyan E; Corbin V; Beytout J; Lebert I; Durand J; Carravieri I; Brun-Jacob A; Frey-Klett P; Baux E; Cazorla C; Eldin C; Hansmann Y; Patrat-Delon S; Prazuck T; Raffetin A; Tattevin P; Vourc'h G; Lesens O; Nguifo EM
Comput Methods Programs Biomed; 2022 Mar; 215():106624. PubMed ID: 35051835
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]