NCT03877614

Artificial Intelligence With Deep Learning and Genes on Cardiovascular Disease

Application of Artificial Intelligence Deep Learning to the Correlation Between Cardiovascular Disease and Individualized Differences

• Status: Unknown
• Phase: —
• Study type: Observational
• Enrollment: 5,000 (estimated)
• Sponsor: National Cheng-Kung University Hospital · Academic / Other
• Sex: All
• Age: 18 Years
• Healthy volunteers: Not accepted

Summary

An association study with large database from electronic medical record system, images, outcome analysis and genetic single nucleotide polymorphism variations by machine learning and artificial intelligence methods in a Taiwanese and Chinese medical center based population

Detailed description

In recent years, the analysis of big data database combined with computer deep learning has gradually played an important role in biomedical technology. For a large number of medical record data analysis, image analysis, single nucleotide polymorphism difference analysis, etc., all relevant research on the development and application of artificial intelligence can be observed extensively. For clinical indication, patients may receive a variety of cardiovascular routine examination and treatments, such as: cardiac ultrasound, multi-path ECG, cardiovascular and peripheral angiography, intravascular ultrasound and optical coherence tomography, electrical physiology, etc... The current study is for the investigative cardiovascular team to take the advantage that in addition to the examination and treatment the participants should appropriately receive, the investigators can also analyze the individual differences and using the "deep learning methodology" to analyze the difference in physical fitness, therapeutic effectiveness and the consideration in the safety of the treatment. The additional goal of this study is to improve the quality of health care, the realization of cardiovascular "precise medicine" especially with personal difference on genetic variation. This study will analyze the differences in the individualization of cardiovascular disease between diseases and other subjects to further improve the quality of care for clinical patients. By using artificial intelligence deep learning system, the investigators hope to not only improve the diagnostic rate and also gain more accurately predict the patient's recovery, improve medical quality in the near future.

Conditions

• Cardiovascular Diseases

Interventions

Type	Name	Description
OTHER	ASCVD risk score	ASCVD score\< 10% will be in the control or low-risk group

Timeline

• Start date: 2018-08-28
• Primary completion: 2021-12-01
• Completion: 2022-06-01
• First posted: 2019-03-15
• Last updated: 2019-03-15

Locations

1 site across 1 country: Taiwan