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Machine Learning Driven Biomarker Selection for Medical Diagnosis
May 20, 2024, 4:42 a.m. | Divyagna Bavikadi, Ayushi Agarwal, Shashank Ganta, Yunro Chung, Lusheng Song, Ji Qiu, Paulo Shakarian
cs.LG updates on arXiv.org arxiv.org
Abstract: Recent advances in experimental methods have enabled researchers to collect data on thousands of analytes simultaneously. This has led to correlational studies that associated molecular measurements with diseases such as Alzheimer's, Liver, and Gastric Cancer. However, the use of thousands of biomarkers selected from the analytes is not practical for real-world medical diagnosis and is likely undesirable due to potentially formed spurious correlations. In this study, we evaluate 4 different methods for biomarker selection and …
abstract advances alzheimer's arxiv cancer cs.ai cs.lg data diagnosis diseases experimental however machine machine learning medical q-bio.qm researchers studies type
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