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"Big Data" Analyses Underlie Clinical Discoveries at the Aortic Institute.

Authors :
Zafar MA
Ziganshin BA
Li Y
Ostberg NP
Rizzo JA
Tranquilli M
Mukherjee SK
Elefteriades JA
Source :
The Yale journal of biology and medicine [Yale J Biol Med] 2023 Sep 29; Vol. 96 (3), pp. 427-440. Date of Electronic Publication: 2023 Sep 29 (Print Publication: 2023).
Publication Year :
2023

Abstract

This issue of the Yale Journal of Biology and Medicine ( YJBM ) focuses on Big Data and precision analytics in medical research. At the Aortic Institute at Yale New Haven Hospital, the vast majority of our investigations have emanated from our large, prospective clinical database of patients with thoracic aortic aneurysm (TAA), supplemented by ultra-large genetic sequencing files. Among the fundamental clinical and scientific discoveries enabled by application of advanced statistical and artificial intelligence techniques on these clinical and genetic databases are the following: From analysis of Traditional "Big Data" (Large data sets) . 1. Ascending aortic aneurysms should be resected at 5 cm to prevent dissection and rupture. 2. Indexing aortic size to height improves aortic risk prognostication. 3. Aortic root dilatation is more malignant than mid-ascending aortic dilatation. 4. Ascending aortic aneurysm patients with bicuspid aortic valves do not carry the poorer prognosis previously postulated. 5. The descending and thoracoabdominal aorta are capable of rupture without dissection. 6. Female patients with TAA do more poorly than male patients. 7. Ascending aortic length is even better than aortic diameter at predicting dissection. 8. A "silver lining" of TAA disease is the profound, lifelong protection from atherosclerosis. From Modern "Big Data" Machine Learning/Artificial Intelligence analysis : 1. Machine learning models for TAA: outperforming traditional anatomic criteria. 2. Genetic testing for TAA and dissection and discovery of novel causative genes. 3. Phenotypic genetic characterization by Artificial Intelligence. 4. Panel of RNAs "detects" TAA. Such findings, based on (a) long-standing application of advanced conventional statistical analysis to large clinical data sets, and (b) recent application of advanced machine learning/artificial intelligence to large genetic data sets at the Yale Aortic Institute have advanced the diagnosis and medical and surgical treatment of TAA.<br /> (Copyright ©2023, Yale Journal of Biology and Medicine.)

Details

Language :
English
ISSN :
1551-4056
Volume :
96
Issue :
3
Database :
MEDLINE
Journal :
The Yale journal of biology and medicine
Publication Type :
Academic Journal
Accession number :
37780996
Full Text :
https://doi.org/10.59249/LNDZ2964