Zobrazeno 1 - 10
of 41
pro vyhledávání: '"Man Hung"'
Autor:
Wei Li, Man Hung, Weicong Su, Eric S. Hon, Xiaoming Sheng, Yao He, Richard Holubkov, Sharon Su, Martin S. Lipsky
Publikováno v:
Risk Management and Healthcare Policy. 13:2047-2056
Introduction It is unknown whether patients admitted for all-cause dental conditions (ACDC) are at high risk for hospital readmission, or what are the risk factors for dental hospital readmission. Objective We examined the prevalence of, and risk fac
Publikováno v:
ICRA
Visuomotor control (VMC) is an effective means of achieving basic manipulation tasks such as pushing or pick-and-place from raw images. Conditioning VMC on desired goal states is a promising way of achieving versatile skill primitives. However, commo
Autor:
Bianca Ruiz-Negrón, Megan N. Rosales, Weicong Su, Wei Li, Jerry Bounsanga, Man Hung, Evelyn Lauren, Frank W. Licari, Julie Xu, Maren W. Voss
Publikováno v:
Gerodontology
Objective This study sought to utilise machine learning methods in artificial intelligence to select the most relevant variables in classifying the presence and absence of root caries and to evaluate the model performance. Background Dental caries is
Autor:
Yao He, Sharon Su, Xiaoming Sheng, Weicong Su, Martin S. Lipsky, Man Hung, Richard Holubkov, Wei Li, Eric S. Hon
Publikováno v:
BDJ Open
BDJ Open, Vol 7, Iss 1, Pp 1-7 (2021)
BDJ Open, Vol 7, Iss 1, Pp 1-7 (2021)
Introduction Hospital readmission rates are an indicator of the health care quality provided by hospitals. Applying machine learning (ML) to a hospital readmission database offers the potential to identify patients at the highest risk for readmission
Publikováno v:
ICRA
End-to-end visuomotor control is emerging as a compelling solution for robot manipulation tasks. However, imitation learning-based visuomotor control approaches tend to suffer from a common limitation, lacking the ability to recover from an out-of-di
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9cdf8ea3f4ab94fd3ec1fa65cdf6cab0
Autor:
Jakob Hjorth von Stemann, Christian Brieghel, Bruno Ledergerber, Christen Lykkegaard Andersen, Michael A. E. Andersen, Jasmin Bahlo, Cameron Ross MacPherson, Alexander T. Pearson, Jens D Lundgren, Magnus Fontes, Rudi Agius, Michael Hallek, Man-Hung Eric Tang, Carsten Utoft Niemann, Jan Larsen, Jacob Bergstedt, Mette Rose Jørgensen, Yoram Louzoun, Carmen D. Herling, Alessandro Cozzi-Lepri
Publikováno v:
Nature Communications
Nature Communications, Vol 11, Iss 1, Pp 1-17 (2020)
Agius, R, Brieghel, C, Andersen, M A, Pearson, A T, Ledergerber, B, Cozzi-Lepri, A, Louzoun, Y, Andersen, C L, Bergstedt, J, von Stemann, J H, Jørgensen, M, Tang, M H E, Fontes, M, Bahlo, J, Herling, C D, Hallek, M, Lundgren, J, MacPherson, C R, Larsen, J & Niemann, C U 2020, ' Machine learning can identify newly diagnosed patients with CLL at high risk of infection ', Nature Communications, vol. 11, no. 1, 363 . https://doi.org/10.1038/s41467-019-14225-8
Agius, R, Brieghel, C, Andersen, M A, Pearson, A T, Ledergerber, B, Cozzi-Lepri, A, Louzoun, Y, Andersen, C L, Bergstedt, J, von Stemann, J H, Jørgensen, M, Tang, M-H E, Fontes, M, Bahlo, J, Herling, C D, Hallek, M, Lundgren, J, MacPherson, C R, Larsen, J & Niemann, C U 2020, ' Machine learning can identify newly diagnosed patients with CLL at high risk of infection ', Nature Communications, vol. 11, no. 1, 363 . https://doi.org/10.1038/s41467-019-14225-8
Nature Communications, Vol 11, Iss 1, Pp 1-17 (2020)
Agius, R, Brieghel, C, Andersen, M A, Pearson, A T, Ledergerber, B, Cozzi-Lepri, A, Louzoun, Y, Andersen, C L, Bergstedt, J, von Stemann, J H, Jørgensen, M, Tang, M H E, Fontes, M, Bahlo, J, Herling, C D, Hallek, M, Lundgren, J, MacPherson, C R, Larsen, J & Niemann, C U 2020, ' Machine learning can identify newly diagnosed patients with CLL at high risk of infection ', Nature Communications, vol. 11, no. 1, 363 . https://doi.org/10.1038/s41467-019-14225-8
Agius, R, Brieghel, C, Andersen, M A, Pearson, A T, Ledergerber, B, Cozzi-Lepri, A, Louzoun, Y, Andersen, C L, Bergstedt, J, von Stemann, J H, Jørgensen, M, Tang, M-H E, Fontes, M, Bahlo, J, Herling, C D, Hallek, M, Lundgren, J, MacPherson, C R, Larsen, J & Niemann, C U 2020, ' Machine learning can identify newly diagnosed patients with CLL at high risk of infection ', Nature Communications, vol. 11, no. 1, 363 . https://doi.org/10.1038/s41467-019-14225-8
Infections have become the major cause of morbidity and mortality among patients with chronic lymphocytic leukemia (CLL) due to immune dysfunction and cytotoxic CLL treatment. Yet, predictive models for infection are missing. In this work, we develop
Publikováno v:
ICASSP
We investigate the problem of machine learning with mislabeled training data. We try to make the effects of mislabeled training better understood through analysis of the basic model and equations that characterize the problem. This includes results a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::99c94e101a911902a2cba2c398dcb32b
http://arxiv.org/abs/1909.09136
http://arxiv.org/abs/1909.09136
Autor:
Weicong Su, Julie Xu, Wei Li, Maren W. Voss, Man Hung, Frank W. Licari, Megan N. Rosales, Yao He, Evelyn Lauren, Bianca Ruiz-Negrón
Publikováno v:
SN Applied Sciences. 1
Resource mismanagement along with the underutilization of dental care has led to serious health and economic consequences. Artificial intelligence was applied to a national health database to develop recommendations for dental care. The data were obt
Autor:
Weicong Su, Eric S. Hon, Bianca Ruiz-Negrón, Jacob O’Brien, Tanner Barton, Megan N. Rosales, Evelyn Lauren, Julie Xu, Man Hung, Wei Li
Publikováno v:
Journal of Personalized Medicine
Volume 10
Issue 3
Journal of Personalized Medicine, Vol 10, Iss 82, p 82 (2020)
Volume 10
Issue 3
Journal of Personalized Medicine, Vol 10, Iss 82, p 82 (2020)
Atrial fibrillation (AF) cases are expected to increase over the next several decades, due to the rise in the elderly population. One promising treatment option for AF is catheter ablation, which is increasing in use. We investigated the hospital rea
Publikováno v:
INTERSPEECH