ReviewCurrent Alzheimer research2025
Recent Advances in the Application of Artificial Intelligence in Alzheimer's Disease.
Review in Current Alzheimer research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) refers to a system that can simulate and execute the processes of human thinking and learning, and make informed decisions. Fueled by the development of AI, the quality and effectiveness of medical work have gained momentum. AI technology plays an increasingly important role in healthcare, exhibiting substantial potential in clinical practice and decision-making processes. In Alzheimer's disease (AD), where early diagnosis and treatment remain challenging due to clinical heterogeneity and insidious progression, AI could offer excellent solutions. AI models can integrate multi-modal data to identify pre-symptomatic biomarkers and stratify high-risk cohorts, improving diagnostic accuracy, assisting with personalizing treatment and care. Furthermore, AI can accelerate drug discovery and development through drug-target identification and predictive modeling of compound efficacy. However, data quality, supervision, transparency, privacy, and ethical concerns need to be addressed. By identifying and retrieving studies for the systematic review, this article provides a comprehensive overview of current progress and related AI applications in AD.
Indexed as
Identifiers
41133841What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.