Zobrazeno 1 - 10
of 42
pro vyhledávání: '"David A. Roffman"'
Autor:
Gregory R. Hart, Vanessa Yan, Bradley J. Nartowt, David A. Roffman, Gigi Stark, Wazir Muhammad, Jun Deng
Publikováno v:
Frontiers in Artificial Intelligence, Vol 5 (2023)
Despite large investment cancer continues to be a major source of mortality and morbidity throughout the world. Traditional methods of detection and diagnosis such as biopsy and imaging, tend to be expensive and have risks of complications. As data b
Externí odkaz:
https://doaj.org/article/2cb1cc909ab14854b8a7f4dbfae3f717
Publikováno v:
PLoS ONE, Vol 13, Iss 10, p e0205264 (2018)
The objective of this study is to train and validate a multi-parameterized artificial neural network (ANN) based on personal health information to predict lung cancer risk with high sensitivity and specificity. The 1997-2015 National Health Interview
Externí odkaz:
https://doaj.org/article/52f78e5045894b8084b1aee37990a1a5
Autor:
Gregory R. Hart, Jun Deng, Issa Ali, David A. Roffman, James B. Yu, Michael S. Leapman, Fangliang L Guo
Publikováno v:
JCO Clinical Cancer Informatics. :1-10
Purpose To develop and validate a multiparameterized artificial neural network (ANN) on the basis of personal health information for prostate cancer risk prediction and stratification. Methods The 1997 to 2015 National Health Interview Survey adult s
Publikováno v:
Scientific Reports, Vol 8, Iss 1, Pp 1-7 (2018)
Scientific Reports
Scientific Reports
Ultraviolet radiation (UVR) exposure and family history are major associated risk factors for the development of non-melanoma skin cancer (NMSC). The objective of this study was to develop and validate a multi-parameterized artificial neural network
Publikováno v:
Big Data in Radiation Oncology
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5ceb78918dc1da1631d43f9f66894194
https://doi.org/10.1201/9781315207582-16
https://doi.org/10.1201/9781315207582-16
Publikováno v:
Big Data in Radiation Oncology
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::20b776f4cb96ca93ff923ed7e5f4c7ca
https://doi.org/10.1201/9781315207582-9
https://doi.org/10.1201/9781315207582-9
Autor:
Issa Ali, Bradley J. Nartowt, Ying Liang, Wazir Muhammad, David A. Roffman, Jun Deng, Xavier Llor, Gregory R. Hart
Publikováno v:
PLoS ONE, Vol 14, Iss 8, p e0221421 (2019)
PLoS ONE
PLoS ONE
Colorectal cancer (CRC) is third in prevalence and mortality among all cancers in the US. Currently, the United States Preventative Services Task Force (USPSTF) recommends anyone ages 50-75 and/or with a family history to be screened for CRC. To impr
Autor:
Bradley J. Nartowt, Jun Deng, Wazir Muhammad, Gregory R. Hart, Ying Liang, David A. Roffman, Issa Ali
Publikováno v:
International Journal of Radiation Oncology*Biology*Physics. 102:e319-e320
Autor:
David S. Roffman
Publikováno v:
Journal of Pharmacy Practice. 29:239-249
A review of the literature was conducted for clinical trials evaluating the antiplatelet P2Y12 receptor antagonists, clopidogrel, prasugrel, and ticagrelor, as well as the guidelines for the management of acute coronary syndrome (ACS) or myocardial i
Publikováno v:
PLoS ONE
PLoS ONE, Vol 13, Iss 10, p e0205264 (2018)
PLoS ONE, Vol 13, Iss 10, p e0205264 (2018)
The objective of this study is to train and validate a multi-parameterized artificial neural network (ANN) based on personal health information to predict lung cancer risk with high sensitivity and specificity. The 1997-2015 National Health Interview