This programme addresses key challenges in cardiovascular disease (CVD) and hypertension management, focusing on the emerging role of artificial intelligence (AI) in cardiovascular (CV) care, the progression from hypertension to CVD, sex-specific risk related to menopause, the four pillars of heart failure with reduced ejection fraction (HFrEF) treatment, and patient adherence following a CVD diagnosis. Recent advances in AI show strong potential to improve CV diagnosis, risk prediction, clinical decision-making, remote monitoring, and patient phenotyping [Elias, 2024; Belenkov, 2025; Teshale, 2024; Tremamunno, 2025]. Applications include imaging, wearables, echocardiography, angiography, and genetics, offering levels of accuracy not previously achievable [Ose, 2024; Bota, 2024]. However, robust validation is required to address issues related to training, equity, real-world performance, and ethical challenges [Guha, 2025; Shaikh, 2025]. Hypertension remains the strongest causal risk factor for CVD [Fuchs, 2020], with evidence supporting BP lowering across all stages of disease [Pfeffer, 2016; McCarthy, 2024]. Mechanisms driving progression include genetic susceptibility, psychosocial stress, sympathetic activation, and the gut–immune axis [Varghese, 2024; Landsbergis, 2025; Shinohara, 2024; Dinakis, 2024]. CVD risk in women rises with age and menopause, particularly with early menopause, obesity, reproductive factors, and pregnancy-related conditions [Uddenberg, 2024; Younis, 2024; Freitas, 2025; Theodorou, 2024]. Guideline-directed HFrEF therapy includes four pillars—ARNI/ACEi/ARB, beta-blockers, MRAs, and SGLT2 inhibitors—with vericiguat emerging as a potential fifth option in selected patients [McDonagh, 2021; Heidenreich, 2022; Beghini, 2025]. Finally, adherence to CVD management is influenced by patient, system, and social factors, with improved outcomes linked to multidisciplinary support, digital tools, and lifestyle interventions [Burnier, 2019; Rashidi, 2020; Lisy, 2025].