Artificial Intelligence Assisted Lifestyle Counseling in Preventive Cardiology a Clinician in the Loop Perspective
Lifestyle counseling is central to cardiovascular prevention, yet recommendations may be difficult to communicate within routine consultations and to translate into feasible daily actions. This perspective proposes a clinician supervised framework in which artificial intelligence helps draft patient readable lifestyle plans from explicitly approved clinical instructions. The framework separates deterministic safety rules and curated clinical content from language generation; a template system without machine learning is recognized as a valid alternative. Personalization is limited to clinician verified information and patient stated preferences, including language, food affordability, and practical access to physical activity. Proposed safeguards include data minimization, version controlled source material, documented review, patient clarification, and escalation when inputs are incomplete or conflicting. Particular attention is given to professional accountability, health literacy, digital exclusion, and the possibility that fluent drafts encourage superficial verification. Lifestyle advice is not assumed to be inherently safe, especially in patients with multimorbidity. This article presents a conceptual proposal rather than an evaluated intervention or systematic review. A staged research agenda compares the approach with high quality nonautomated counseling materials and measures safety, comprehension, clinician workload, equity, and sustained behavior change. Any benefit remains to be established empirically; the intended contribution is a testable model of accountable health communication rather than a claim of improved cardiovascular outcomes.
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