Intelligent platforms for disease assessment: novel approaches in functional echocardiography.
Accelerating trends in the dynamic digital era (from 2004 onward) has resulted in the emergence of novel parametric imaging tools that allow easy and accurate extraction of quantitative information from cardiac images. This review principally attempts to heighten the awareness of newer emerging paradigms that may advance acquisition, visualization and interpretation of the large functional data sets obtained during cardiac ultrasound imaging. Incorporation of innovative cognitive software that allow advanced pattern recognition and disease forecasting will likely transform the human-machine interface and interpretation process to achieve a more efficient and effective work environment. Novel technologies for automation and big data analytics that are already active in other fields need to be rapidly adapted to the health care environment with new academic-industry collaborations to enrich and accelerate the delivery of newer decision making tools for enhancing patient care.
Zena and Michael A. Wiener Cardiovascular Institute, Icahn Mount Sinai School of Medicine, New York, New York. Electronic address: partho.sengupta@mountsinai.org.
Partho P
PP
Sengupta
D001185:Artificial Intelligence / Q000639:trends; D057205:Automation, Laboratory; D004059:Diffusion of Innovation; D004452:Echocardiography / Q000379:methods* / Q000639:trends; D005544:Forecasting; D006331:Heart Diseases / Q000000981:diagnostic imaging*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D016247:Information Storage and Retrieval; D010363:Pattern Recognition, Automated; D011237:Predictive Value of Tests; D011379:Prognosis; D012720:Severity of Illness Index; D012984:Software
big data; cognitive computing; echocardiography; parametric imaging; robotics