A - 4 The Potential Applications of Software Supporting the Early Detection of Cognitive Disorders and Dementia in Diagnostics and Prevention

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Abstract Objective In Hungary, the process of diagnosing dementia is slow and time-consuming. Currently, there are no well-developed systems and strategies at the local level for screening, and there is no artificial intelligence algorithm that could determine early signs of dementia based on the patient’s digital behavioral patterns. Methods Two PILOTs were conducted using the PreDem platform. Over the PILOTs’ duration (2021.09.01.-2024.04.09), 61,902 test data were analyzed. The 259 participants completed SDMT-type tests, Stroop tests, and memory/word games. Results We established a unified system for task evaluation, facilitating cross-test result comparisons. Participants (n = 43,902) were grouped into three categories: 1st - presumed dementia patients (13,932), 2nd - diagnosed MS patients (16,175), and 3rd - presumably normal population (13,795). Comparing the first two groups to the normal population revealed significant differences, vividly illustrated by density functions. A key finding is the substantial improvement in individuals dealing with memory disorders and forgetfulness through regular cognitive game performance. Conclusion Study results reveal the PreDem platform’s potential as a valuable tool for early dementia detection and prevention. Combining cognitive tests and artificial intelligence, the platform can successfully identify early signs of dementia and cognitive impairment (90% accuracy), potentially leading to early diagnosis, treatment, and improved quality of life for patients and families.

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