Evidence generation is a multistep process that remains labor-intensive and time-consuming. Although artificial intelligence (AI)-enabled platforms support literature reviews, their complete automation is scarce. We utilized an online AI suite, SymproAI, to perform a fully automated targeted literature review (TLR) on treatment outcomes in patients with aquaporin-4 (AQP4)-positive neuromyelitis optica spectrum disorder (NMOSD) and compared its performance with the manual process. This TLR summarizes the efficacy and safety of Food and Drug Administration-approved biologics or conventional immunosuppressants in patients with AQP4-positive NMOSD using SymproAI. Performance was validated using sensitivity, specificity, predictive values, overall accuracy, and overall speed of performance. SymproAI searches demonstrated 98.2% agreement with the manual retrieval (1,721 vs. 1,691 citations). For title/abstract and full-text screening, SymproAI achieved 94.4% and 80.5% accuracy, respectively. SymproAI generated TLR-identified 44 publications identical to those provided by the manual review. Overall, the TLR timeframe was estimated at ~120 min using SymproAI, compared with 96 work hours required for the manual process. The generative feature of SymproAI demonstrated good agreement with human findings and data interpretation. Both processes agreed on eculizumab with the strongest relapse-prevention efficacy (94.2% risk reduction), followed by satralizumab (74–79%) and inebilizumab (73%). Across conventional therapies, rituximab demonstrated superior relapse prevention compared with these oral immunosuppressants (mycophenolate mofetil and azathioprine), reducing relative relapse risk by ~60% ( p = 0.046), highlighting its greater efficacy. SymproAI enables rapid, accurate, and reproducible automation of TLRs without compromising study selection or clinical conclusions, supporting accelerated and methodologically rigorous evidence synthesis in time-sensitive clinical settings.
Objectives: Dengue and Japanese Encephalitis (JE) are significant mosquito-borne viral diseases posing serious public health challenges in Assam. Both diseases caused by viruses from the Flaviviridae family share Aedes and Culex mosquitoes as their primary vectors. Karbi Anglong is one of the most affected districts in the state and country, necessitating a detailed investigation into the healthcare challenges. This study aims to determine the awareness level, availability of healthcare services, and other contributing factors to the occurrence of Dengue and JE in Karbi Anglong through a qualitative approach. Materials and Methods: For this study, a targeted sample was selected from the population, comprising various age groups, health workers, community heads, and a mixed population. Specific criteria were considered for selecting individual participants. The study employed in-depth interviews, key informant interviews, and focus group discussions as data collection methods. A total of 135 participants took part in the interviews and discussions. Results: Several factors contributing to the disease’s propagation were highlighted by participants during interviews and discussions. These included low awareness levels, inadequate municipal roles, high population density in some selected areas, and preference for traditional approaches over medical care, socio-economic status, and the presence of migrant populations. The healthcare facilities were inadequate to handle the dengue outbreak in the years 2022–2023. Conclusion: The study identified major causes influencing the prevalence of these diseases in Karbi Anglong. Respondents also offered necessary suggestions, emphasizing that community awareness and mitigation efforts were lacking. Strengthening these efforts could help prevent the occurrence and prevalence of these diseases in the region.
