Heart disease remains a leading cause of morbidity and mortality globally, straining healthcare systems worldwide. Artificial intelligence (AI) offers transformative solutions in cardiology, enhancing early diagnosis, personalized treatment, and surgical precision. This review examines the impact of AI on cardiology, focusing on its role in analyzing medical images, predicting risk, and managing chronic diseases. AI algorithms and intense learning models have demonstrated exceptional proficiency in interpreting imaging modalities, surpassing human diagnostic capabilities. Predictive analytics models utilizing electronic health records, genomic data, and lifestyle information significantly improve early detection and risk prediction of heart conditions. In addition, AI facilitates personalized treatment plans by predicting patient responses to specific medications and adjusting therapies in real time. In chronic disease management, AI-powered wearable devices and telehealth platforms enable continuous monitoring and timely interventions, reducing hospital readmissions. Furthermore, AI enhances surgical outcomes through real-time assistance and precision. While AI’s potential in cardiology is vast, ethical considerations and challenges such as data privacy, bias, and the “black box” nature of some algorithms must be addressed. AI stands poised to revolutionize cardiovascular medicine, offering promising avenues for improved patient outcomes and healthcare efficiency.

Background: The pathological changes in the lining of blood vessels associated with diabetes are a well‐established risk factor for stroke, with some studies suggesting a two times increase in risk compared to non‐diabetics.Methods: Death certificates from the CDC WONDER (Centers for Disease Control and Prevention Wide‐Ranging OnLine Data for Epidemiologic Research) database were examined from 1999 to 2019 for ischemic stroke‐related mortality in patients with type 2 diabetes mellitus (T2DM). Annual percent change (APC) and age‐adjusted mortality rates (AAMRs) per 100,000 persons were calculated and stratified by year, sex, and race/ethnicity.Results: From 1999 to 2019 there were 18,135 deaths from ischemic stroke in patients with T2DM. The AAMR remained relatively constant from 0.31 in 1999 to 0.32 in 2004, gradually declining to 0.14 in 2014 (APC: −6.74), followed by a rapid increase to 0.44 in 2017 (APC: 53.11). Men showed consistently higher AAMR than women in 1999 (AAMR men: 0.34 vs. women: 0.29) and 2019 (AAMR men: 0.55 vs. women: 0.42). When comparing race, African Americans (AA) presented with a consistently higher AAMR in 1999 (AAMR AA: 0.4 vs. white: 0.29) and in 2019 (AAMR AA: 0.62 vs. white:0.44). Notably, a significant escalation in AAMR occurred from 2014 to 2019, affecting both populations; this trend reached its pinnacle in 2019 (2016 AAMR AA: 0.4 vs. white: 0.26) (2019 AAMR AA: 0.62 vs. white: 0.44).Conclusion: The findings highlight fluctuating trends in AAMRs with distinct shifts observed after 2014. Noteworthy gender and racial disparities in AAMRs were also evident. The study emphasises the need for ongoing vigilance and focused interventions to address the evolving dynamics of ischaemic stroke‐related mortality in the T2DM population.

Background: Acute myocardial infarction (AMI) remains a leading cause of mortality in the USA, particularly among individuals aged 65 and older. There is limited research about the association between psychoactive substance use and cardiovascular death due to AMI. This study aims to analyze trends in AMI‐related mortality among older adults (aged ≥ 65) associated with psychoactive substance use in the USA from 1999 to 2020, with a focus on demographic and geographic variations.Methods: We conducted a descriptive analysis using death certificates from the CDC's WONDER database. Data were extracted for age, sex, race/ethnicity, urban–rural status, and geographic region. Crude mortality rates and AAMR were calculated, and temporal trends were assessed using Joinpoint regression.Results: Between 1999 and 2020, there were 231 359 AMI‐related deaths among older adults with substance use disorders. Men (39.2) had a markedly higher mortality rate than women (15.0). Mortality rates increased across all age groups, with the most pronounced rise in those aged 85 and older (33.9). Metropolitan areas (22.3) experienced lower mortality rates than nonmetropolitan areas (37.9). The Midwest (32.3) consistently recorded the highest mortality rates, followed by the Northeast (25.0), South (24.5), and West (18.7).Conclusion: The study reveals notable temporal trends in AMI mortality among older adults with psychoactive substance use, highlighting significant demographic and regional disparities. These findings underscore the need for targeted interventions to address this growing public health issue.