<?xml version="1.0" encoding="UTF-8"?><rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcq="http://purl.org/dc/terms/"><records count="1" morepages="false" start="1" end="1"><record rownumber="1"><dc:product_type>Conference Paper</dc:product_type><dc:title>Class-balanced deep learning with adaptive vector scaling loss for dementia stage detection</dc:title><dc:creator>Tong, Boning; Zhou, Zhuoping; Ataee-Tarzanagh, Davoud; Hou, Bojian; Saykin, Andrew J; Moore, Jason; Ritchie, Marylyn; Shen, Li</dc:creator><dc:corporate_author/><dc:editor/><dc:description/><dc:publisher>Springer</dc:publisher><dc:date>2023-10-08</dc:date><dc:nsf_par_id>10509423</dc:nsf_par_id><dc:journal_name>MLMI’23: The 14th International Workshop on Machine Learning in Medical Imaging</dc:journal_name><dc:journal_volume/><dc:journal_issue/><dc:page_range_or_elocation/><dc:issn/><dc:isbn/><dc:doi>https://doi.org/10.1007/978-3-031-45676-3_15</dc:doi><dcq:identifierAwardId>1837964</dcq:identifierAwardId><dc:subject/><dc:version_number/><dc:location>Vancouver, Canada</dc:location><dc:rights/><dc:institution/><dc:sponsoring_org>National Science Foundation</dc:sponsoring_org></record></records></rdf:RDF>