Machine-learning models based on histological images from healthy donors identify imageQTLs and predict chronological age.
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| Title: | Machine-learning models based on histological images from healthy donors identify imageQTLs and predict chronological age. |
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| Authors: | Meng R; Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520.; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520., Zhu W; Department of Computer Sciences, Yale University, New Haven, CT 06520., Cameron CJF; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520.; Department of Radiology and Biomedical Imaging, Yale University, New Haven, CT 06520., Ni P; Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520.; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520., Zhou X; Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520.; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520., Ulammandakh T; Department of Computer Sciences, Yale University, New Haven, CT 06520., Gerstein MB; Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520.; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520.; Department of Computer Sciences, Yale University, New Haven, CT 06520.; Department of Statistics and Data Science, Yale University, New Haven, CT 06520.; Department of Biomedical Informatics and Data Science, Yale University, New Haven, CT 06520. |
| Source: | Proceedings of the National Academy of Sciences of the United States of America [Proc Natl Acad Sci U S A] 2025 Nov 18; Vol. 122 (46), pp. e2423469122. Date of Electronic Publication: 2025 Nov 11. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: National Academy of Sciences Country of Publication: United States NLM ID: 7505876 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1091-6490 (Electronic) Linking ISSN: 00278424 NLM ISO Abbreviation: Proc Natl Acad Sci U S A Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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