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Background: There is limited research on the intra‐individual efficacy of ventricular pacing minimization algorithms developed by Biotronik—the Ventricular Pace Suppression algorithm (VpS) and the Intrinsic Rhythm Support plus algorithm (IRSplus) (BIOTRONIK SE & Co. KG, Berlin, Germany). We performed a randomized pilot trial that evaluated the efficacy of two algorithms in patients with symptomatic sinus node dysfunction (SND) who received a dual‐chamber pacemaker. Methods: The trial was conducted in 11 tertiary hospitals in South Korea. The patients were randomized to either the VpS or IRSplus algorithm group after a 3‐month period of fixed atrioventricular (AV) delay. The primary outcome was the ventricular pacing percentage (Vp%) at each follow‐up visit. The secondary outcomes were the occurrence of heart failure (HF) and atrial fibrillation (AF) during the study period. Results: Data from 131 patients were analyzed. Initially, their average Vp% over 3 months with a fixed AV interval was 14.1 ± 19.4%. Patients were randomly assigned to VpS and IRSplus groups, with 66 and 65 in each. Algorithms reduced average Vp% to 4.0 ± 11.3% at 9 months and 6.7 ± 14.9% at 15 months. These algorithms were more effective for patients with paced AV delay (PAVD) ≤300 ms compared to those with PAVD >300 ms. Both algorithms were equally effective in reducing Vp%. Clinical AF or HF hospitalization was not observed during the study period. Conclusion: The VpS and IRSplus algorithms are effective and safe in minimizing unnecessary ventricular pacing in patients with SND. [ABSTRACT FROM AUTHOR]

The growing interest in intelligent automation adoption and development in tourism presents many potential solutions for sustainable tourism issues. To map the current landscape of research on intelligent automation in sustainable tourism, a systematic review was conducted of 213 scholarly articles. Five major themes were identified: intelligent automation to enhance tourist experience, preserve heritage, promote quality of life, measure tourist experience, and conserve the environment. Scholarly work on this topic has paid more attention to the economic and sociocultural aspects of sustainability but less to addressing environmental issues. To uncover further research gaps, this study outlines sustainability transition pathways using two dimensions: sustainability inclusion and tourist involvement. Twenty-three distinct AI-based innovations were mapped onto the pathways to reveal future research directions. The findings explain the lack of AI-based solutions that offer high levels of sustainability inclusion and tourist involvement. Thus, this study proposes the "AI4GoodTourism" framework, inferring that intelligent automation with high sustainability inclusion levels can scale up the marginal contributions that tourists provide collectively. This framework serves to guide future research and development for various stakeholders who are progressing sustainable tourism agendas through intelligent automation. [ABSTRACT FROM AUTHOR]