Mohammad A Zafar, Bulat A Ziganshin, Yupeng Li, Nicolai P Ostberg, John A Rizzo, Maryann Tranquilli, Sandip K Mukherjee, John A Elefteriades
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引用次数: 0
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.
期刊介绍:
The Yale Journal of Biology and Medicine (YJBM) is a graduate and medical student-run, peer-reviewed, open-access journal dedicated to the publication of original research articles, scientific reviews, articles on medical history, personal perspectives on medicine, policy analyses, case reports, and symposia related to biomedical matters. YJBM is published quarterly and aims to publish articles of interest to both physicians and scientists. YJBM is and has been an internationally distributed journal with a long history of landmark articles. Our contributors feature a notable list of philosophers, statesmen, scientists, and physicians, including Ernst Cassirer, Harvey Cushing, Rene Dubos, Edward Kennedy, Donald Seldin, and Jack Strominger. Our Editorial Board consists of students and faculty members from Yale School of Medicine and Yale University Graduate School of Arts & Sciences. All manuscripts submitted to YJBM are first evaluated on the basis of scientific quality, originality, appropriateness, contribution to the field, and style. Suitable manuscripts are then subject to rigorous, fair, and rapid peer review.