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Social Determinants of Health and Racial Disparities in Cardiac Events in Breast Cancer
CONCLUSIONS: Neighborhood and built environment variables are the most important SDOH predictors for 2-year MACE, and NHB patients were more likely to have unfavorable SDOH conditions. This finding reinforces that race is a social construct.PMID:37433439 | DOI:10.6004/jnccn.2023.7023
Source: Journal of the National Comprehensive Cancer Network : JNCCN - July 11, 2023 Category: Cancer & Oncology Authors: Nickolas Stabellini Mantas Dmukauskas Marcio S Bittencourt Jennifer Cullen Amie J Barda Justin X Moore Susan Dent Husam Abdel-Qadir Aniket A Kawatkar Ambarish Pandey John Shanahan Jill S Barnholtz-Sloan Kristin A Waite Alberto J Montero Avirup Guha Source Type: research

Prediction of short-term atrial fibrillation risk using primary care electronic health records
Conclusions FIND-AF, a machine learning algorithm applicable at scale in routinely collected primary care data, identifies people at higher risk of short-term AF.
Source: Heart - June 26, 2023 Category: Cardiology Authors: Nadarajah, R., Wu, J., Hogg, D., Raveendra, K., Nakao, Y. M., Nakao, K., Arbel, R., Haim, M., Zahger, D., Parry, J., Bates, C., Cowan, C., Gale, C. P. Tags: Open access, Editor's choice Arrhythmias and sudden death Source Type: research

Sensors, Vol. 23, Pages 5618: Automated Signal Quality Assessment of Single-Lead ECG Recordings for Early Detection of Silent Atrial Fibrillation
s D. Zink Atrial fibrillation (AF) is an arrhythmic cardiac disorder with a high and increasing prevalence in aging societies, which is associated with a risk for stroke and heart failure. However, early detection of onset AF can become cumbersome since it often manifests in an asymptomatic and paroxysmal nature, also known as silent AF. Large-scale screenings can help identifying silent AF and allow for early treatment to prevent more severe implications. In this work, we present a machine learning-based algorithm for assessing signal quality of hand-held diagnostic ECG devices to prevent misclassification due to insu...
Source: Sensors - June 15, 2023 Category: Biotechnology Authors: Markus Lueken Michael Gramlich Steffen Leonhardt Nikolaus Marx Matthias D. Zink Tags: Article Source Type: research

Cardiovascular disease (CVD) outcomes and associated risk factors in a medicare population without prior CVD history: an analysis using statistical and machine learning algorithms
AbstractThere is limited information on predicting incident cardiovascular outcomes among high- to very high-risk populations such as the elderly ( ≥ 65 years) in the absence of prior cardiovascular disease and the presence of non-cardiovascular multi-morbidity. We hypothesized that statistical/machine learning modeling can improve risk prediction, thus helping inform care management strategies. We defined a population from the Medicare he alth plan, a US government-funded program mostly for the elderly and varied levels of non-cardiovascular multi-morbidity. Participants were screened for cardiovascular disease (CVD)...
Source: Internal and Emergency Medicine - June 9, 2023 Category: Emergency Medicine Source Type: research

Association of brain microbleeds with risk factors, cognition, and MRI markers in MESA
DISCUSSION: Results suggest differing associations for lobar versus deep locations. Sensitive microbleed quantification will facilitate future longitudinal studies of their potential role as an early indicator of vascular pathology.PMID:37289978 | DOI:10.1002/alz.13346
Source: The Journal of Alzheimers Association - June 8, 2023 Category: Psychiatry Authors: Paul N Jensen Tanweer Rashid Jeffrey B Ware Yuhan Cui Colleen M Sitlani Thomas R Austin W T Longstreth Alain G Bertoni Elizabeth Mamourian R Nick Bryan Ilya M Nasrallah Mohamad Habes Susan R Heckbert Source Type: research

Social bias in artificial intelligence algorithms designed to improve cardiovascular risk assessment relative to the Framingham Risk Score: a protocol for a systematic review
This study will employ an equity-lens to identify sources of bias (ie, race/ethnicity, gender and social stratum) in ML algorithms designed to improve CVD risk assessment relative to the FRS. A comprehensive literature search will be completed using MEDLINE, Embase and IEEE to answer the research question: do AI algorithms that are designed for the estimation of CVD risk and that compare performance with the FRS address the sources of bias inherent in the FRS? No study date filters will be imposed on the search, but English language filters will be applied. Studies describing a specific algorithm or ML approach that provid...
Source: BMJ Open - May 31, 2023 Category: General Medicine Authors: Garcha, I., Phillips, S. P. Tags: Open access, General practice / Family practice Source Type: research

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