## 8 Conclusions
Aggregated data from the automated skin pathology detection system supports population health management, helping healthcare institutions identify trends in skin cancer prevalence and allocate resources more efficiently. Interoperability within the EHR ensures accessibility of skin cancer screening results to authorized healthcare providers, promoting communication and healthcare continuity while avoiding redundant screenings. Early detection of ocular diseases through the automated system allows for prompt intervention and treatment initiation, which is crucial in preserving vision and preventing irreversible damage. Integrating automated detection systems into EHRs streamlines the diagnostic process, providing healthcare professionals with effortless access to complete medical records for quick decision making and personalized treatment planning. Continuous monitoring of patients' ocular health over time allows for the prompt identification of subtle changes, leading to early diagnosis and management. The early detection of ocular diseases contributes to cost reduction by minimizing resource requirements and preventing complications that necessitate extensive treatments. Additionally, automated detection systems support remote monitoring and telemedicine, facilitating healthcare consultations even for patients in remote or underserved areas. The EHR's capability to capture and store longitudinal data enables retrospective analysis, offering insights into disease progression, treatment effectiveness, and outcomes. Aggregated and anonymized data from integrated automated detection systems can significantly contribute to research and population health studies, unveiling trends, risk factors, and treatment outcomes, ultimately aiding in the development of more effective strategies for early detection and treatment. The implementation of an automated classification module for diagnosis is not designed to replace the role of doctors or supplant medical opinion. Rather, it serves as a complementary tool aimed at enhancing diagnostic capabilities and supporting healthcare professionals in their decision-making processes. The module's purpose is to streamline data analysis and provide additional insights to aid in accurate diagnosis, while ultimately empowering physicians to make informed decisions based on their expertise and clinical judgment. Conceptualization, methodology, software, validation and formal analysis, A.-M.S. and N.-R.R. ; investigation, resources, data curation, writing--original draft preparation, writing--review and editing, visualization, project administration A.-M.S. ; supervision E.O. and M.C. ; funding acquisition, M.C. All authors have read and agreed to the published version of the manuscript. This research was funded by POLITEHNICA Bucharest National University of Science and Technology through PubArt doctoral program. The data presented in this study are available on request from the corresponding author due to privacy reasons. Conflicts of Interest: Author [PERSON] was an independent researcher. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.