A review paper published on arXiv details computational methods for analyzing cell-free DNA (cfDNA) to detect multiple cancers early. The paper, covering methods developed between 2022 and 2025, focuses on fragmentomics and epigenetic features. It discusses statistical, machine learning, and deep learning approaches, highlighting multimodal ensemble methods as having the highest readiness for clinical integration, while also noting the need for standardized evaluation protocols. AI
IMPACT This review highlights the increasing application of machine learning and deep learning in medical diagnostics, specifically for early cancer detection.
RANK_REASON The cluster contains a research paper published on arXiv.
- autoencoder-based models
- deep learning
- Fragmentomics
- machine learning
- Multi-canceR Early-detection Test in Asymptomatic Individuals (PREVENT)
- arXiv
- multimodal ensemble approaches
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