Association of Deep Learning-Derived Histologic Features of Placental Chorionic Villi with Maternal and Infant Characteristics in the New Hampshire Birth Cohort Study.

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Title: Association of Deep Learning-Derived Histologic Features of Placental Chorionic Villi with Maternal and Infant Characteristics in the New Hampshire Birth Cohort Study.
Authors: Anderson EC; Department of Epidemiology, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA., Srinivasan G; Department of Pathology and Laboratory Medicine and the Department of Computational Biomedicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA.; University of California, Los Angeles, David Geffen School of Medicine, Los Angeles, CA, USA., Howe CG; Department of Epidemiology, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA., Zhang E; Dartmouth College, Hanover, NH, USA., Jeon C; Thomas Jefferson High School for Science and Technology, Alexandria, VA, USA.; Emerging Diagnostic and Investigative Technologies, Department of Pathology and Laboratory Medicine, Dartmouth Hitchcock Medical Center, Lebanon, NH, USA., Paruchuri GSG; Emerging Diagnostic and Investigative Technologies, Department of Pathology and Laboratory Medicine, Dartmouth Hitchcock Medical Center, Lebanon, NH, USA.; Independence High School, Frisco, TX, USA., Zhang L; Thomas Jefferson High School for Science and Technology, Alexandria, VA, USA.; Emerging Diagnostic and Investigative Technologies, Department of Pathology and Laboratory Medicine, Dartmouth Hitchcock Medical Center, Lebanon, NH, USA., Hwang L; Emerging Diagnostic and Investigative Technologies, Department of Pathology and Laboratory Medicine, Dartmouth Hitchcock Medical Center, Lebanon, NH, USA.; Georgia Institute of Technology, Atlanta, GA, USA., Sengar A; Thomas Jefferson High School for Science and Technology, Alexandria, VA, USA.; Emerging Diagnostic and Investigative Technologies, Department of Pathology and Laboratory Medicine, Dartmouth Hitchcock Medical Center, Lebanon, NH, USA., Reddy N; Emerging Diagnostic and Investigative Technologies, Department of Pathology and Laboratory Medicine, Dartmouth Hitchcock Medical Center, Lebanon, NH, USA.; The University of Texas at Austin, Austin, TX, USA., Karan A; Thomas Jefferson High School for Science and Technology, Alexandria, VA, USA.; Emerging Diagnostic and Investigative Technologies, Department of Pathology and Laboratory Medicine, Dartmouth Hitchcock Medical Center, Lebanon, NH, USA., Chen A; Thomas Jefferson High School for Science and Technology, Alexandria, VA, USA.; Emerging Diagnostic and Investigative Technologies, Department of Pathology and Laboratory Medicine, Dartmouth Hitchcock Medical Center, Lebanon, NH, USA., Shen J; Dartmouth College, Hanover, NH, USA., Owo O; Dartmouth College, Hanover, NH, USA., Caraballo-Bobea Z; Dartmouth College, Hanover, NH, USA., Khatchikian C; Department of Epidemiology, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA., Palys TJ; Department of Epidemiology, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA., Vaickus LJ; Department of Pathology, Dartmouth-Hitchcock Medical Center, Lebanon, NH, USA., Madan JC; Department of Epidemiology, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA., Karagas MR; Department of Epidemiology, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA., Bentz JL; Department of Pathology, Dartmouth-Hitchcock Medical Center, Lebanon, NH, USA., Levy JJ; Department of Epidemiology, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA.; Department of Pathology and Laboratory Medicine and the Department of Computational Biomedicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA.; University of California, Los Angeles, David Geffen School of Medicine, Los Angeles, CA, USA.
Source: MedRxiv : the preprint server for health sciences [medRxiv] 2025 Apr 23. Date of Electronic Publication: 2025 Apr 23.
Publication Type: Journal Article; Preprint
Journal Info: Country of Publication: United States NLM ID: 101767986 Publication Model: Electronic Cited Medium: Internet NLM ISO Abbreviation: medRxiv Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
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  Data: Association of Deep Learning-Derived Histologic Features of Placental Chorionic Villi with Maternal and Infant Characteristics in the New Hampshire Birth Cohort Study.
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