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Purpose Of Review: The past few decades have seen significant technologic innovation for the treatment and diagnosis of cardiovascular diseases. The subsequent growing complexity of modern medicine, however, is causing fundamental challenges in our healthcare system primarily in the spheres of patient involvement, data generation, and timely clinical implementation. The Institute of Medicine advocated for a learning health system (LHS) in which knowledge generation and patient care are inherently symbiotic. The purpose of this paper is to review how the advances in technology and big data have been used to further patient care and data generation and what future steps will need to occur to develop a LHS in cardiovascular disease.
Recent Findings: Patient-centered care has progressed from technologic advances yielding resources like decision aids. LHS can also incorporate patient preferences by increasing and standardizing patient-reported information collection. Additionally, data generation can be optimized using big data analytics by developing large interoperable datasets from multiple sources to allow for real-time data feedback. Developing a LHS will require innovative technologic solutions with a patient-centered lens to facilitate symbiosis in data generation and clinical practice.
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http://dx.doi.org/10.1007/s11883-021-00916-5 | DOI Listing |
J Eval Clin Pract
September 2025
Cochrane Taiwan, Taipei Medical University, Taipei, Taiwan.
Background: Chest radiography is often performed preoperatively as a common diagnostic tool. However, chest radiography carries the risk of radiation exposure. Given the uncertainty surrounding the utility of preoperative chest radiographs, physicians require systematically developed recommendations.
View Article and Find Full Text PDFGenet Med
September 2025
Division of Genetics and Epidemiology, The Institute of Cancer Research, London, UK; The Royal Marsden NHS Foundation Trust, Fulham Road, London, UK. Electronic address:
Purpose: Hereditary Leiomyomatosis and Renal Cell Cancer (HLRCC) is a rare cancer susceptibility syndrome exclusively attributable to pathogenic variants in FH (HGNC:3700). This paper quantitatively weights the phenotypic context (PP4/PS4) of such very rare variants in FH.
Methods: We collated clinical diagnostic testing data on germline FH variants from 387 individuals with HLRCC and 1,780 individuals with renal cancer, and compared the frequency of 'very rare' variants in each phenotypic cohort against 562,295 population controls.
J Cereb Blood Flow Metab
September 2025
Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria.
Functional PET (fPET) identifies stimulation-specific changes of physiological processes, individual molecular connectivity and group-level molecular covariance. Since there is currently no consistent analysis approach available for these techniques, we present a toolbox for unified fPET assessment. The toolbox supports analysis of data obtained with a variety of radiotracers, scanners, experimental protocols, cognitive tasks and species.
View Article and Find Full Text PDFAm J Epidemiol
September 2025
Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
Tree-based scan statistics (TBSS) are data mining methods that screen thousands of hierarchically related health outcomes to detect unsuspected adverse drug effects. TBSS traditionally analyze claims data with outcomes defined via diagnosis codes. TBSS have not been previously applied to rich clinical information in Electronic Health Records (EHR).
View Article and Find Full Text PDFJ Prim Care Community Health
September 2025
Division of Nephrology, Department of Medicine, National University Hospital, Singapore.
Background: Chronic kidney disease (CKD) management was largely centered around renin-angiotensin-aldosterone system inhibitors (RAASi) optimization, until recent emergence of novel therapeutics. However, slow adoption of guideline-directed therapy leaves patients vulnerable to disease progression. In 2022, a data-driven informatics approach was introduced to track real-time adherence to best practices.
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