Zobrazeno 1 - 10
of 54 933
pro vyhledávání: '"So, Neda"'
Autor:
Tavakoli, Neda, Rahsepar, Amir Ali, Benefield, Brandon C., Shen, Daming, López-Tapia, Santiago, Schiffers, Florian, Goldberger, Jeffrey J., Albert, Christine M., Wu, Edwin, Katsaggelos, Aggelos K., Lee, Daniel C., Kim, Daniel
Background: Late Gadolinium Enhancement (LGE) imaging is the gold standard for assessing myocardial fibrosis and scarring, with left ventricular (LV) LGE extent predicting major adverse cardiac events (MACE). Despite its importance, routine LGE-based
Externí odkaz:
http://arxiv.org/abs/2501.01372
Autor:
Elyassirad, Danial, Gheiji, Benyamin, Vatanparast, Mahsa, Ahmadzadeh, Amir Mahmoud, Kamandi, Neda, Soleimanian, Amirmohammad, Salehi, Sara, Faghani, Shahriar
Gliomas are the most common cause of mortality among primary brain tumors. Molecular markers, including Isocitrate Dehydrogenase (IDH) and O[6]-methylguanine-DNA methyltransferase (MGMT) influence treatment responses and prognosis. Deep learning (DL)
Externí odkaz:
http://arxiv.org/abs/2412.21091
The rapid advancement of Generative AI (Gen AI) technologies, particularly tools like ChatGPT, is significantly impacting the labor market by reshaping job roles and skill requirements. This study examines the demand for ChatGPT-related skills in the
Externí odkaz:
http://arxiv.org/abs/2412.07042
Accurate short-term streamflow and flood forecasting are critical for mitigating river flood impacts, especially given the increasing climate variability. Machine learning-based streamflow forecasting relies on large streamflow datasets derived from
Externí odkaz:
http://arxiv.org/abs/2412.04764
Autor:
Hejazi, Neda, Xuan, Jerry W., Coria, David R., Sawczynec, Erica, Crossfield, Ian J. M., Cristofari, Paul I., Zhang, Zhoujian, Rhem, Maleah
The chemical abundance measurements of host stars and their substellar companions provide a powerful tool to trace the formation mechanism of the planetary systems. We present a detailed high-resolution spectroscopic analysis of a young M-type star,
Externí odkaz:
http://arxiv.org/abs/2411.15591
Recent observations by pulsar timing arrays (PTAs) indicate a potential detection of a stochastic gravitational wave (GW) background. Metastable cosmic strings have been recognized as a possible source of the observed signals. In this paper, we propo
Externí odkaz:
http://arxiv.org/abs/2411.13299
Executing drift maneuvers during high-speed cornering presents significant challenges for autonomous vehicles, yet offers the potential to minimize turning time and enhance driving dynamics. While reinforcement learning (RL) has shown promising resul
Externí odkaz:
http://arxiv.org/abs/2411.11762
Autor:
Delgrange, Camille, Demler, Olga, Mora, Samia, Menze, Bjoern, de la Rosa, Ezequiel, Davoudi, Neda
Predicting stroke risk is a complex challenge that can be enhanced by integrating diverse clinically available data modalities. This study introduces a self-supervised multimodal framework that combines 3D brain imaging, clinical data, and image-deri
Externí odkaz:
http://arxiv.org/abs/2411.09822
Autor:
Newlin, Nancy R., Schilling, Kurt, Koudoro, Serge, Chandio, Bramsh Qamar, Kanakaraj, Praitayini, Moyer, Daniel, Kelly, Claire E., Genc, Sila, Chen, Jian, Yang, Joseph Yuan-Mou, Wu, Ye, He, Yifei, Zhang, Jiawei, Zeng, Qingrun, Zhang, Fan, Adluru, Nagesh, Nath, Vishwesh, Pathak, Sudhir, Schneider, Walter, Gade, Anurag, Rathi, Yogesh, Hendriks, Tom, Vilanova, Anna, Chamberland, Maxime, Pieciak, Tomasz, Ciupek, Dominika, Vega, Antonio Tristán, Aja-Fernández, Santiago, Malawski, Maciej, Ouedraogo, Gani, Machnio, Julia, Ewert, Christian, Thompson, Paul M., Jahanshad, Neda, Garyfallidis, Eleftherios, Landman, Bennett A.
Publikováno v:
Machine.Learning.for.Biomedical.Imaging. 2 (2024)
White matter alterations are increasingly implicated in neurological diseases and their progression. International-scale studies use diffusion-weighted magnetic resonance imaging (DW-MRI) to qualitatively identify changes in white matter microstructu
Externí odkaz:
http://arxiv.org/abs/2411.09618
Accurate prediction of cardiovascular diseases remains imperative for early diagnosis and intervention, necessitating robust and precise predictive models. Recently, there has been a growing interest in multi-modal learning for uncovering novel insig
Externí odkaz:
http://arxiv.org/abs/2411.05900