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pro vyhledávání: '"Karaman, Batuhan K."'
Autor:
Karaman, Batuhan K., Zabir, Ishmam, Benhaim, Alon, Chaudhary, Vishrav, Sabuncu, Mert R., Song, Xia
Balancing safety and usefulness in large language models has become a critical challenge in recent years. Models often exhibit unsafe behavior or adopt an overly cautious approach, leading to frequent overrefusal of benign prompts, which reduces thei
Externí odkaz:
http://arxiv.org/abs/2410.12999
Autor:
Nguyen, Minh, Karaman, Batuhan K., Kim, Heejong, Wang, Alan Q., Liu, Fengbei, Sabuncu, Mert R.
Deep learning models can extract predictive and actionable information from complex inputs. The richer the inputs, the better these models usually perform. However, models that leverage rich inputs (e.g., multi-modality) can be difficult to deploy wi
Externí odkaz:
http://arxiv.org/abs/2405.20448
Autor:
Karaman, Batuhan K., Sabuncu, Mert R.
In this study, we employ a transformer encoder model to characterize the significance of longitudinal patient data for forecasting the progression of Alzheimer's Disease (AD). Our model, Longitudinal Forecasting Model for Alzheimer's Disease (LongFor
Externí odkaz:
http://arxiv.org/abs/2405.17352
Breast cancer is one of the leading causes of mortality among women worldwide. Early detection and risk assessment play a crucial role in improving survival rates. Therefore, annual or biennial mammograms are often recommended for screening in high-r
Externí odkaz:
http://arxiv.org/abs/2404.19083
Autor:
Wang, Alan Q., Karaman, Batuhan K., Kim, Heejong, Rosenthal, Jacob, Saluja, Rachit, Young, Sean I., Sabuncu, Mert R.
Interpretability for machine learning models in medical imaging (MLMI) is an important direction of research. However, there is a general sense of murkiness in what interpretability means. Why does the need for interpretability in MLMI arise? What go
Externí odkaz:
http://arxiv.org/abs/2310.01685
Akademický článek
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Autor:
Karaman, Batuhan K.1,2 (AUTHOR), Mormino, Elizabeth C.3 (AUTHOR), Sabuncu, Mert R.1,2 (AUTHOR) msabuncu@cornell.edu
Publikováno v:
PLoS ONE. 11/16/2022, Vol. 17 Issue 11, p1-24. 24p.
