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External validation of a deep learning electrocardiogram algorithm to detect ventricular dysfunction.
In International journal of cardiology ; h5-index 68.0
OBJECTIVE :
BACKGROUND :
METHODS :
RESULTS :
CONCLUSIONS :
Attia Itzhak Zachi, Tseng Andrew S, Benavente Ernest Diez, Inojosa Jose Medina, Clark Taane G, Malyutina Sofia, Kapa Suraj, Schirmer Henrik, Kudryavtsev Alexander V, Noseworthy Peter A, Carter Rickey E, Ryabikov Audrey, Perel Pablo, Friedman Paul A, Leon David A, Lopez-Jimenez Francisco
2021-Jan-02
Artificial intelligence, Electrocardiogram, Left ventricular systolic dysfunction, Machine learning
Structural and functional connectivity of motor circuits after perinatal stroke: A machine learning study.
In NeuroImage. Clinical
Carlson Helen L, Craig Brandon T, Hilderley Alicia J, Hodge Jacquie, Rajashekar Deepthi, Mouches Pauline, Forkert Nils D, Kirton Adam
2020
Diffusion tractography, MRI, Machine learning, Pediatric, Perinatal stroke, Resting state fMRI

Analyzing the vast coronavirus literature with CoronaCentral.
In bioRxiv : the preprint server for biology
Lever Jake, Altman Russ B
2020-Dec-22

On the regularization of feature fusion and mapping for fast MR multi-contrast imaging via iterative networks.
In Magnetic resonance imaging
Liu Xinwen, Wang Jing, Sun Hongfu, Chandra Shekhar S, Crozier Stuart, Liu Feng
2021-Jan-02
Deep learning, Image reconstruction, Magnetic resonance imaging (MRI), Multi-contrast

Active Inference: Demystified and Compared.
In Neural computation
Sajid Noor, Ball Philip J, Parr Thomas, Friston Karl J
2021-Jan-05

Predicting the Ease of Human Category Learning Using Radial Basis Function Networks.
In Neural computation
Roads Brett D, Mozer Michael C
2021-Jan-05
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