The Scope of Practice for Primary Cardiovascular Disease Prevention Expanded to Advanced Practice Providers: What Does the Data Show?

Iqbal, Sajid; Ali, Naheed Feroz; Ladak, Laila Akbar; Shivji, Rozmeen; Zulfiqar, Mehak; Barolia, Rubina

doi:10.1007/s11886-023-01899-2

Cited by 2 publications

(1 citation statement)

References 56 publications

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“…It is estimated that up to 90% of CVD cases can be prevented. 96 Goldstein et al 97 developed an ML model to predict cardiovascular risk by utilizing data from 1944 patients who were initially diagnosed with acute myocardial infarction (AMI). The model incorporated 13 laboratory parameters (calcium, carbon dioxide, creatinine, creatine kinase-MB, HGB, glucose, mean corpuscular volume [MCV], mean corpuscular HGB concentration, platelets, potassium, RDW, sodium, and leukocytes) to forecast disease severity and mortality, revealing a nonlinear correlation between calcium and HGB and post-infarction mortality in patients.…”

Section: Study Of Ai Application In Diagnosis Of Cvdmentioning

confidence: 99%

Integration of artificial intelligence in clinical laboratory medicine: Advancements and challenges

Xie,

Jia,

Liu

2024

Interdisciplinary Medicine

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Artificial intelligence (AI)‐driven analysis of comprehensive clinical parameters is bringing about a significant transformation in traditional routine clinical laboratory testing. This transformation impacts the prediction, prevention, diagnosis, and prognosis of human diseases. AI possesses the capability to efficiently analyze and process vast and intricate datasets, thereby facilitating the development of diverse and efficient diagnostic or predictive models. This advancement is fueling significant improvements in laboratory quality, automation, and the accuracy of diagnoses. In this context, we conducted a thorough review and discussion on the progression of AI applications in clinical laboratory medicine, encompassing advancements, implementation, and challenges. Our conclusion underscores that integrating AI into clinical laboratory testing will notably propel personalized precision medicine forward and enhance diagnostic accuracy, especially benefiting patients for whom accurate diagnoses are elusive through traditional laboratory testing systems.

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Section: Study Of Ai Application In Diagnosis Of Cvdmentioning

confidence: 99%