Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Amirata Ghorbani"'
Autor:
Andre Esteva, Jean Feng, Douwe van der Wal, Shih-Cheng Huang, Jeffry P. Simko, Sandy DeVries, Emmalyn Chen, Edward M. Schaeffer, Todd M. Morgan, Yilun Sun, Amirata Ghorbani, Nikhil Naik, Dhruv Nathawani, Richard Socher, Jeff M. Michalski, Mack Roach, Thomas M. Pisansky, Jedidiah M. Monson, Farah Naz, James Wallace, Michelle J. Ferguson, Jean-Paul Bahary, James Zou, Matthew Lungren, Serena Yeung, Ashley E. Ross, NRG Prostate Cancer AI Consortium, Howard M. Sandler, Phuoc T. Tran, Daniel E. Spratt, Stephanie Pugh, Felix Y. Feng, Osama Mohamad
Publikováno v:
npj Digital Medicine, Vol 5, Iss 1, Pp 1-8 (2022)
Abstract Prostate cancer is the most frequent cancer in men and a leading cause of cancer death. Determining a patient’s optimal therapy is a challenge, where oncologists must select a therapy with the highest likelihood of success and the lowest l
Externí odkaz:
https://doaj.org/article/54fe1e7fc7644b949b66c889805f2d44
Autor:
Andre Esteva, Jean Feng, Douwe van der Wal, Shih-Cheng Huang, Jeffry P. Simko, Sandy DeVries, Emmalyn Chen, Edward M. Schaeffer, Todd M. Morgan, Yilun Sun, Amirata Ghorbani, Nikhil Naik, Dhruv Nathawani, Richard Socher, Jeff M. Michalski, Mack Roach, Thomas M. Pisansky, Jedidiah M. Monson, Farah Naz, James Wallace, Michelle J. Ferguson, Jean-Paul Bahary, James Zou, Matthew Lungren, Serena Yeung, Ashley E. Ross, NRG Prostate Cancer AI Consortium, Howard M. Sandler, Phuoc T. Tran, Daniel E. Spratt, Stephanie Pugh, Felix Y. Feng, Osama Mohamad
Publikováno v:
npj Digital Medicine, Vol 6, Iss 1, Pp 1-2 (2023)
Externí odkaz:
https://doaj.org/article/7d8e50289fd743a593f6ff3df5d018ef
Autor:
Siyi Tang, Amirata Ghorbani, Rikiya Yamashita, Sameer Rehman, Jared A. Dunnmon, James Zou, Daniel L. Rubin
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-9 (2021)
Abstract The reliability of machine learning models can be compromised when trained on low quality data. Many large-scale medical imaging datasets contain low quality labels extracted from sources such as medical reports. Moreover, images within a da
Externí odkaz:
https://doaj.org/article/115fcccb74764f0687b45ec863822f0b
Autor:
Amirata Ghorbani, David Ouyang, Abubakar Abid, Bryan He, Jonathan H. Chen, Robert A. Harrington, David H. Liang, Euan A. Ashley, James Y. Zou
Publikováno v:
npj Digital Medicine, Vol 3, Iss 1, Pp 1-10 (2020)
Abstract Echocardiography uses ultrasound technology to capture high temporal and spatial resolution images of the heart and surrounding structures, and is the most common imaging modality in cardiovascular medicine. Using convolutional neural networ
Externí odkaz:
https://doaj.org/article/914a9b08ef9d49d596f7dc8d8a6c2fa6
Autor:
Mahdi Mahdavi, Hadi Choubdar, Erfan Zabeh, Michael Rieder, Safieddin Safavi-Naeini, Zsolt Jobbagy, Amirata Ghorbani, Atefeh Abedini, Arda Kiani, Vida Khanlarzadeh, Reza Lashgari, Ehsan Kamrani
Publikováno v:
PLoS ONE, Vol 16, Iss 7, p e0252384 (2021)
Early prediction of patient mortality risks during a pandemic can decrease mortality by assuring efficient resource allocation and treatment planning. This study aimed to develop and compare prognosis prediction machine learning models based on invas
Externí odkaz:
https://doaj.org/article/e888857cfdf94eaca6d63c9c52b33954
Publikováno v:
Information, Vol 13, Iss 1, p 15 (2021)
Interpretability is becoming an active research topic as machine learning (ML) models are more widely used to make critical decisions. Tabular data are one of the most commonly used modes of data in diverse applications such as healthcare and finance
Externí odkaz:
https://doaj.org/article/291c858522f94d45a8fb4147f15e2e37
Publikováno v:
AAAI
In order for machine learning to be deployed and trusted in many applications, it is crucial to be able to reliably explain why the machine learning algorithm makes certain predictions. For example, if an algorithm classifies a given pathology image
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f38718ed1ba102724e248ec8cb35d6cf
https://doi.org/10.1609/aaai.v33i01.33013681
https://doi.org/10.1609/aaai.v33i01.33013681
Autor:
Amirata Ghorbani, Reza Lashgari, Zsolt Jobbagy, Safieddin Safavi-Naeini, Arda Kiani, Ehsan Kamrani, Mahdi Mahdavi, Atefeh Abedini, Vida Khanlarzadeh, Hadi Choubdar, Michael J. Rieder, Erfan Zabeh
Publikováno v:
PLoS ONE, Vol 16, Iss 7, p e0252384 (2021)
PLoS ONE
Paediatrics Publications
PLoS ONE
Paediatrics Publications
Early prediction of patient mortality risks during a pandemic can decrease mortality by assuring efficient resource allocation and treatment planning. This study aimed to develop and compare prognosis prediction machine learning models based on invas
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f763186dec58f38a94383cc8ffdf66bb
https://doaj.org/article/e888857cfdf94eaca6d63c9c52b33954
https://doaj.org/article/e888857cfdf94eaca6d63c9c52b33954
Autor:
Mahdi Mahdavi, Hadi Choubdar, Erfan Zabeh, Michael Rieder, Safieddin Safavi-Naeini, Vida Khanlarzadeh, Zsolt Jobbagy, Amirata Ghorbani, Atefeh Abedini, Arda Kiani, Reza Lashgari, Ehsan Kamrani
With no effective treatment currently available and maximum preventive measures already in place, more interventions in the clinical field are needed to decrease COVID-19 patient mortality. Early prediction of mortality risk in COVID-19 patients can
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a6ed57e21eb0bc18855bd912825c5a89
https://doi.org/10.21203/rs.3.rs-86363/v1
https://doi.org/10.21203/rs.3.rs-86363/v1
Autor:
Sameer Rehman, James Zou, Amirata Ghorbani, Daniel L. Rubin, Siyi Tang, Rikiya Yamashita, Jared Dunnmon
Publikováno v:
Scientific Reports
Scientific Reports, Vol 11, Iss 1, Pp 1-9 (2021)
Scientific Reports, Vol 11, Iss 1, Pp 1-9 (2021)
The reliability of machine learning models can be compromised when trained on low quality data. Many large-scale medical imaging datasets contain low quality labels extracted from sources such as medical reports. Moreover, images within a dataset may
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7a7d0acac98ab5657be215d1a603fca2
https://pubmed.ncbi.nlm.nih.gov/33863957
https://pubmed.ncbi.nlm.nih.gov/33863957