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This study aims to prevent the development of dementia in individuals with mild cognitive impairment (MCI) through innovative solutions for early detection, precision diagnostics, and individualized evidence-based prevention and treatment.The epidemiological part will focus on two aspects: the impact of depression and sleep disturbances on cognitive impairment and dementia development and use register data and AI to develop a risk prediction model to identify people at risk for MCI, Alzheimer disease, and other dementia early in primary health care. Both risk factors and protective factors will be examined, thus the model will suggest individuals who should be further evaluated for MCI, Alzheimer´s, and other forms of dementia and provide support for preventive advice and interventions.The clinical part aims to determine the clinical and health economic value of a precision diagnostic algorithm based on a combination of digital cognitive tests and blood-based biomarkers in the assessment of subjective cognitive complaints (SCC) in primary care. The study will actively screen for SCC among individuals at increased risk of dementia, with risk factors including age, hypertension, and/or type II diabetes mellitus. Digital cognitive tests and blood-based biomarkers will be utilized to diagnose SCC, mild cognitive impairment (MCI), and dementia due to Alzheimer´s disease, as well as to examine how these biomarkers predict disease conversion after two years.