Background/Objectives: This systematic review explores the integration of digital and AI-enhanced cognitive behavioral therapy (CBT) for insomnia, focusing on underlying neurocognitive mechanisms and associated clinical outcomes. Insomnia significantly impairs cognitive functioning, overall health, and quality of life. Although traditional CBT has demonstrated efficacy, its scalability and ability to deliver individualized care remain limited. Emerging AI-driven interventions-including chatbots, mobile applications, and web-based platforms-present innovative avenues for delivering more accessible and personalized insomnia treatments. Methods: Following PRISMA guidelines, this review synthesized findings from 78 studies published between 2004 and 2024. A systematic search was conducted across PubMed, Scopus, Web of Science, and PsycINFO. Studies were included based on predefined criteria prioritizing randomized controlled trials (RCTs) and high-quality empirical research that evaluated AI-augmented CBT interventions targeting sleep disorders, particularly insomnia. Results: The findings suggest that digital and AI-enhanced CBT significantly improves sleep parameters, patient adherence, satisfaction, and the personalization of therapy in alignment with individual neurocognitive profiles. Moreover, these technologies address critical limitations of conventional CBT, notably those related to access and scalability. AI-based tools appear especially promising in optimizing treatment delivery and adapting interventions to cognitive-behavioral patterns. Conclusions: While AI-enhanced CBT demonstrates strong potential for advancing insomnia treatment through neurocognitive personalization and broader clinical accessibility, several challenges persist. These include uncertainties surrounding long-term efficacy, practical implementation barriers, and ethical considerations. Future large-scale longitudinal research is necessary to confirm the sustained neurocognitive and behavioral benefits of digital and AI-powered CBT for insomnia.

Achalasia is a rare and complex esophageal disease of unknown etiology characterized by difficulty in swallowing due to the lack of opening of the lower esophageal sphincter and the absence of esophageal peristalsis. Recent advancements in technology for analyzing DNA, RNA and biomolecules in high-throughput techniques are offering new opportunities to better understand the etiology and the pathogenetic mechanisms underlying achalasia. Through this narrative review of the scientific literature, we aim to provide a comprehensive assessment of the state-of-the-art knowledge on omics of achalasia, with particular attention to those considered relevant to the pathogenesis of the disease. The notion and importance of the multi-omics approach, its limitations and future directions are also introduced, and it is highlighted how the integration of single omics data will lead to new insights into the development of achalasia and offer clinical tools which will allow early diagnosis and better patient management.