Institution
University of Southern California
Education•Los Angeles, California, United States•
About: University of Southern California is a education organization based out in Los Angeles, California, United States. It is known for research contribution in the topics: Population & Cancer. The organization has 73160 authors who have published 169955 publications receiving 7838906 citations. The organization is also known as: USC & University of Southern CA.
Topics: Population, Cancer, Poison control, Medicine, Breast cancer
Papers published on a yearly basis
Papers
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Michael S. Lawrence1, Carrie Sougnez1, Lee Lichtenstein1, Kristian Cibulskis1 +306 more•Institutions (26)
TL;DR: It is shown that human-papillomavirus-associated tumours are dominated by helical domain mutations of the oncogene PIK3CA, novel alterations involving loss of TRAF3, and amplification of the cell cycle gene E2F1.
Abstract: The Cancer Genome Atlas profiled 279 head and neck squamous cell carcinomas (HNSCCs) to provide a comprehensive landscape of somatic genomic alterations Here we show that human-papillomavirus-associated tumours are dominated by helical domain mutations of the oncogene PIK3CA, novel alterations involving loss of TRAF3, and amplification of the cell cycle gene E2F1 Smoking-related HNSCCs demonstrate near universal loss-of-function TP53 mutations and CDKN2A inactivation with frequent copy number alterations including amplification of 3q26/28 and 11q13/22 A subgroup of oral cavity tumours with favourable clinical outcomes displayed infrequent copy number alterations in conjunction with activating mutations of HRAS or PIK3CA, coupled with inactivating mutations of CASP8, NOTCH1 and TP53 Other distinct subgroups contained loss-of-function alterations of the chromatin modifier NSD1, WNT pathway genes AJUBA and FAT1, and activation of oxidative stress factor NFE2L2, mainly in laryngeal tumours Therapeutic candidate alterations were identified in most HNSCCs
2,997 citations
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TL;DR: A system for recognizing human faces from single images out of a large database containing one image per person, based on a Gabor wavelet transform, which is constructed from a small get of sample image graphs.
Abstract: We present a system for recognizing human faces from single images out of a large database containing one image per person. Faces are represented by labeled graphs, based on a Gabor wavelet transform. Image graphs of new faces are extracted by an elastic graph matching process and can be compared by a simple similarity function. The system differs from the preceding one (Lades et al., 1993) in three respects. Phase information is used for accurate node positioning. Object-adapted graphs are used to handle large rotations in depth. Image graph extraction is based on a novel data structure, the bunch graph, which is constructed from a small get of sample image graphs.
2,934 citations
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Johns Hopkins University1, University of Utah2, University of Rochester3, The Royal Marsden NHS Foundation Trust4, National Institutes of Health5, Stanford University6, Washington University in St. Louis7, Ontario Institute for Cancer Research8, University of Sydney9, St. Jude Medical Center10, University of Toronto11, Mayo Clinic12, American Society of Clinical Oncology13, University of Southern California14, North Carolina State University15, Indiana University16, University of Milan17, University of Michigan18
TL;DR: The Update Committee recommends that HER2 status (HER2 negative or positive) be determined in all patients with invasive breast cancer on the basis of one or more HER2 test results (negative, equivocal, or positive).
Abstract: Purpose
To update the American Society of Clinical Oncology (ASCO)/College of American Pathologists (CAP) guideline recommendations for human epidermal growth factor receptor 2 (HER2) testing in breast cancer to improve the accuracy of HER2 testing and its utility as a predictive marker in invasive breast cancer.
2,934 citations
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Jeffrey D. Stanaway1, Ashkan Afshin1, Emmanuela Gakidou1, Stephen S Lim1 +1050 more•Institutions (346)
TL;DR: This study estimated levels and trends in exposure, attributable deaths, and attributable disability-adjusted life-years (DALYs) by age group, sex, year, and location for 84 behavioural, environmental and occupational, and metabolic risks or groups of risks from 1990 to 2017 and explored the relationship between development and risk exposure.
2,910 citations
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01 Jan 1992TL;DR: The mapping is proved to be capable of approximating any real continuous function on a compact set to arbitrary accuracy and applications to truck backer-upper control and time series prediction problems are presented.
Abstract: A general method is developed to generate fuzzy rules from numerical data. The method consists of five steps: divide the input and output spaces of the given numerical data into fuzzy regions; generate fuzzy rules from the given data; assign a degree of each of the generated rules for the purpose of resolving conflicts among the generated rules; create a combined fuzzy rule base based on both the generated rules and linguistic rules of human experts; and determine a mapping from input space to output space based on the combined fuzzy rule base using a defuzzifying procedure. The mapping is proved to be capable of approximating any real continuous function on a compact set to arbitrary accuracy. Applications to truck backer-upper control and time series prediction problems are presented. >
2,892 citations
Authors
Showing all 73925 results
Name | H-index | Papers | Citations |
---|---|---|---|
Eric S. Lander | 301 | 826 | 525976 |
Trevor W. Robbins | 231 | 1137 | 164437 |
Edward Witten | 202 | 602 | 204199 |
Irving L. Weissman | 201 | 1141 | 172504 |
John C. Morris | 183 | 1441 | 168413 |
Paul M. Thompson | 183 | 2271 | 146736 |
Terrie E. Moffitt | 182 | 594 | 150609 |
John R. Yates | 177 | 1036 | 129029 |
Michael I. Jordan | 176 | 1016 | 216204 |
Russel J. Reiter | 169 | 1646 | 121010 |
George P. Chrousos | 169 | 1612 | 120752 |
Jiawei Han | 168 | 1233 | 143427 |
Zena Werb | 168 | 473 | 122629 |
Douglas F. Easton | 165 | 844 | 113809 |
Bruce L. Miller | 163 | 1153 | 115975 |