Zobrazeno 1 - 10
of 229
pro vyhledávání: '"Hallak, Joelle A."'
Autor:
Alam, Minhaj Nur, Yamashita, Rikiya, Ramesh, Vignav, Prabhune, Tejas, Lim, Jennifer I., Chan, R. V. P., Hallak, Joelle, Leng, Theodore, Rubin, Daniel
Self supervised contrastive learning based pretraining allows development of robust and generalized deep learning models with small, labeled datasets, reducing the burden of label generation. This paper aims to evaluate the effect of CL based pretrai
Externí odkaz:
http://arxiv.org/abs/2208.11563
Deep learning models have shown promising results in a wide range of computer vision applications across various domains. The success of deep learning methods relies heavily on the availability of a large amount of data. Deep neural networks are pron
Externí odkaz:
http://arxiv.org/abs/2111.00042
Autor:
Aleem, Abdullah, Nallabothula, Manoj Prabhakar, Setabutr, Pete, Hallak, Joelle A., Yi, Darvin
Blepharoptosis, or ptosis as it is more commonly referred to, is a condition of the eyelid where the upper eyelid droops. The current diagnosis for ptosis involves cumbersome manual measurements that are time-consuming and prone to human error. In th
Externí odkaz:
http://arxiv.org/abs/2106.03905
Autor:
Mojab, Nooshin, Noroozi, Vahid, Aleem, Abdullah, Nallabothula, Manoj P., Baker, Joseph, Azar, Dimitri T., Rosenblatt, Mark, Chan, RV Paul, Yi, Darvin, Yu, Philip S., Hallak, Joelle A.
Data from clinical real-world settings is characterized by variability in quality, machine-type, setting, and source. One of the primary goals of medical computer vision is to develop and validate artificial intelligence (AI) based algorithms on real
Externí odkaz:
http://arxiv.org/abs/2104.02609
Autor:
Mojab, Nooshin, Noroozi, Vahid, Yi, Darvin, Nallabothula, Manoj Prabhakar, Aleem, Abdullah, Yu, Phillip S., Hallak, Joelle A.
With promising results of machine learning based models in computer vision, applications on medical imaging data have been increasing exponentially. However, generalizations to complex real-world clinical data is a persistent problem. Deep learning m
Externí odkaz:
http://arxiv.org/abs/2007.12672
Akademický článek
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Autor:
Banerjee, Imon, de Sisternes, Luis, Hallak, Joelle, Leng, Theodore, Osborne, Aaron, Durbin, Mary, Rubin, Daniel
We propose a hybrid sequential deep learning model to predict the risk of AMD progression in non-exudative AMD eyes at multiple timepoints, starting from short-term progression (3-months) up to long-term progression (21-months). Proposed model combin
Externí odkaz:
http://arxiv.org/abs/1902.10700
Autor:
Cole, Emily, Valikodath, Nita G., Al-Khaled, Tala, Bajimaya, Sanyam, KC, Sagun, Chuluunbat, Tsengelmaa, Munkhuu, Bayalag, Jonas, Karyn E., Chuluunkhuu, Chimgee, MacKeen, Leslie D., Yap, Vivien, Hallak, Joelle, Ostmo, Susan, Wu, Wei-Chi, Coyner, Aaron S., Singh, Praveer, Kalpathy-Cramer, Jayashree, Chiang, Michael F., Campbell, J. Peter, Chan, R. V. Paul
Publikováno v:
In Ophthalmology Science December 2022 2(4)
Autor:
Scanzera, Angelica C., Shorter, Ellen, Kinnaird, Charles, Valikodath, Nita, Al-Khaled, Tala, Cole, Emily, Kravets, Sasha, Hallak, Joelle A., McMahon, Timothy, Chan, R.V. Paul
Publikováno v:
In Journal of Optometry 2022 15 Supplement 1:S91-S97
Akademický článek
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