Stent as a Novel Technology for Coronary Artery Disease and Their Clinical Manifestation

Ullah, Muneeb; Wahab, Abdul; Khan, Shahid Ullah; Zaman, Umber; Rehman, Khalil ur; Hamayun, Shah; Naeem, Muhammad; Ali, Haider; Riaz, Tayyaba; Saeed, Sumbul; Alsuhaibani, Amnah Mohammed; Refat, Moamen S.

doi:10.1016/j.cpcardiol.2022.101415

Cited by 47 publications

(15 citation statements)

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“…As mobile devices become more ubiquitous, integrating mHealth solutions into accounting fintech can provide healthcare organizations with real-time financial data and patient information (Askari, Ghofrani & Taherdoost, 2024, Ullah, et. al., 2023).…”

Section: Future Trends and Considerationsmentioning

confidence: 99%

Integrating accounting fintech innovations in the U. S. healthcare sector: opportunities, challenges, and impacts on financial management and patient care

Olubusola Odeyemi

2024

World J. Adv. Res. Rev.

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Integrating accounting fintech innovations in the U.S. healthcare sector presents significant opportunities for enhancing financial management and patient care. This paper examines the current landscape of accounting fintech solutions in healthcare, highlighting key opportunities, challenges, and impacts on financial management and patient care. The healthcare industry is increasingly adopting fintech innovations to streamline financial processes, improve efficiency, and enhance patient care. Accounting fintech solutions such as automated billing and payment systems, blockchain technology for secure transactions, and predictive analytics for financial forecasting are revolutionizing financial management practices in healthcare organizations. However, integrating accounting fintech innovations in the healthcare sector also presents several challenges. These include concerns about data security and privacy, the need for regulatory compliance, and the potential for disruption to traditional financial management practices. Addressing these challenges will be crucial to realizing the full potential of accounting fintech in healthcare. The impact of integrating accounting fintech innovations in the U.S. healthcare sector is significant. Improved financial management practices can lead to cost savings, increased revenue, and better resource allocation, ultimately benefiting both healthcare organizations and patients. Additionally, enhanced financial transparency and efficiency can lead to improved patient care outcomes and experiences. In conclusion, integrating accounting fintech innovations in the U.S. healthcare sector offers numerous opportunities for improving financial management and patient care. However, this integration also presents challenges that must be addressed to realize these benefits fully. By overcoming these challenges and leveraging the potential of accounting fintech, healthcare organizations can enhance their financial management practices and provide better care to their patients.

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Section: Future Trends and Considerationsmentioning

confidence: 99%

Integrating accounting fintech innovations in the U. S. healthcare sector: opportunities, challenges, and impacts on financial management and patient care

Olubusola Odeyemi

2024

World J. Adv. Res. Rev.

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“…Genome-wide association studies have identified several genetic variants linked to CAD [7][8][9][10]. Additionally, epidemiological studies have identified significant socioeconomic, race, and sex disparities in CAD prevalence, quality measures, and outcomes [1,[11][12][13]. Further work has found that a combination of genetic, demographic, and environmental factors contributes to the severity of CAD and other cardiovascular diseases [1,[14][15][16][17].…”

Section: Introductionmentioning

confidence: 99%

Use of machine learning to identify risk factors for coronary artery disease

Huang

2023

PLoS ONE

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Coronary artery disease (CAD) is the leading cause of death in both developed and developing nations. The objective of this study was to identify risk factors for coronary artery disease through machine-learning and assess this methodology. A retrospective, cross-sectional cohort study using the publicly available National Health and Nutrition Examination Survey (NHANES) was conducted in patients who completed the demographic, dietary, exercise, and mental health questionnaire and had laboratory and physical exam data. Univariate logistic models, with CAD as the outcome, were used to identify covariates that were associated with CAD. Covariates that had a p<0.0001 on univariate analysis were included within the final machine-learning model. The machine learning model XGBoost was used due to its prevalence within the literature as well as its increased predictive accuracy in healthcare prediction. Model covariates were ranked according to the Cover statistic to identify risk factors for CAD. Shapely Additive Explanations (SHAP) explanations were utilized to visualize the relationship between these potential risk factors and CAD. Of the 7,929 patients that met the inclusion criteria in this study, 4,055 (51%) were female, 2,874 (49%) were male. The mean age was 49.2 (SD = 18.4), with 2,885 (36%) White patients, 2,144 (27%) Black patients, 1,639 (21%) Hispanic patients, and 1,261 (16%) patients of other race. A total of 338 (4.5%) of patients had coronary artery disease. These were fitted into the XGBoost model and an AUROC = 0.89, Sensitivity = 0.85, Specificity = 0.87 were observed (Fig 1). The top four highest ranked features by cover, a measure of the percentage contribution of the covariate to the overall model prediction, were age (Cover = 21.1%), Platelet count (Cover = 5.1%), family history of heart disease (Cover = 4.8%), and Total Cholesterol (Cover = 4.1%). Machine learning models can effectively predict coronary artery disease using demographic, laboratory, physical exam, and lifestyle covariates and identify key risk factors.

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“…Moreover, plaque buildup in the arteries which is known as coronary artery disease (CAD) is one of a rising cause of death around the world. The CAD is a cardiovascular condition characterized by the narrowing of blood arteries, specifically the coronary artery, resulting in reduced blood supply to the myocardium [27]. Moreover, the coronary heart disease is widely recognized as the primary cause of mortality and morbidity in developed nations [28].…”

Section: Introductionmentioning

confidence: 99%

3D printed auxetic stents with re-entrant and chiral topologies

Alomarah,

Al-Ibraheemi,

Ruan

2023

Smart Mater. Struct.

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The mechanical performance of the medical stent is crucial and of key significance to the dependability and reliability of the stent-plaque-artery system. In this study, an auxetic stent, namely, re-entrant chiral auxetic (RCA) is proposed. Two types of stent (RCA-X and RCA-Y) are proposed. The RCA stents are designed through a periodic distribution of two dimensional (2D) RCA cells along both the circumferential and axial directions. A set of polyimide specimens were 3d printed using Multi-Jet Fusion (MJF) process. The compressive properties of the 3d printed stents were experimentally examined, while the tensile properties were numerically investigated. Results showed that the RCA-X stent revealed a remarkable radial expansion (i.e. auxetic features) of approximately 50% while the RCA-Y stent showed radial expansion of 16.7% . Despite the auxetic features of the compressed stents, asymmetric deformation patterns were resulted in the case of the RCA-X while uniform patterns were resulted in the case of the RCA-Y. The FE models were further employed to examined the effects of number of unit cells along the circumferential direction on the auxetic features. The auxetic features of the developed stents could be controlled by adjusting the geometric parameters of the RCA’s cell and number of cells along the circumferential direction. The promising properties of the RCA stents might sheds the light on the design auxetic stents for practical clinical applications.

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Stent as a Novel Technology for Coronary Artery Disease and Their Clinical Manifestation

Cited by 47 publications

References 1 publication

Integrating accounting fintech innovations in the U. S. healthcare sector: opportunities, challenges, and impacts on financial management and patient care

Integrating accounting fintech innovations in the U. S. healthcare sector: opportunities, challenges, and impacts on financial management and patient care

Use of machine learning to identify risk factors for coronary artery disease

3D printed auxetic stents with re-entrant and chiral topologies

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