Echocardiographic Detection of Regional Wall Motion Abnormalities Using Artificial Intelligence Compared to Human Readers.
Jeremy A SlivnickNils T GessertJuan I CotellaLucas OliveiraNicola PezzottiParastou EslamiAli SadeghiSimon WehleDavid PrabhuIrina Waechter-StehleAshish M ChaudhariTeodora SzaszLinda LeeMarie AltenburgGiancarlo SaldanaMichael RandazzoJeanne M DeCaraKarima AddetiaVictor Mor-AviRoberto M LangPublished in: Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography (2024)
Deep learning provides accurate detection of RWMA, which was comparable to experts and outperformed a majority of novices. Deep learning may improve the efficiency of RWMA assessment and serve as a teaching tool for novices.
Keyphrases
- deep learning
- artificial intelligence
- big data
- machine learning
- convolutional neural network
- loop mediated isothermal amplification
- endothelial cells
- real time pcr
- label free
- mitral valve
- pulmonary hypertension
- left ventricular
- high resolution
- induced pluripotent stem cells
- pluripotent stem cells
- medical students
- left atrial
- quantum dots