Zobrazeno 1 - 10
of 861
pro vyhledávání: '"Polydorides, A."'
Autor:
Chen, Shengjia, Campanella, Gabriele, Elmas, Abdulkadir, Stock, Aryeh, Zeng, Jennifer, Polydorides, Alexandros D., Schoenfeld, Adam J., Huang, Kuan-lin, Houldsworth, Jane, Vanderbilt, Chad, Fuchs, Thomas J.
Recent advances in artificial intelligence (AI), in particular self-supervised learning of foundation models (FMs), are revolutionizing medical imaging and computational pathology (CPath). A constant challenge in the analysis of digital Whole Slide I
Externí odkaz:
http://arxiv.org/abs/2407.07841
Chronic Obstructive Pulmonary Disease (COPD) can be fatal and is challenging to live with due to its severe symptoms. Pulmonary rehabilitation (PR) is one of the managements means to maintain COPD in a stable status. However, implementation of PR in
Externí odkaz:
http://arxiv.org/abs/2310.14342
Autor:
Campanella, Gabriele, Kwan, Ricky, Fluder, Eugene, Zeng, Jennifer, Stock, Aryeh, Veremis, Brandon, Polydorides, Alexandros D., Hedvat, Cyrus, Schoenfeld, Adam, Vanderbilt, Chad, Kovatch, Patricia, Cordon-Cardo, Carlos, Fuchs, Thomas J.
Recent breakthroughs in self-supervised learning have enabled the use of large unlabeled datasets to train visual foundation models that can generalize to a variety of downstream tasks. While this training paradigm is well suited for the medical doma
Externí odkaz:
http://arxiv.org/abs/2310.07033
Autor:
Lung, Robert, Polydorides, Nick
We consider the inverse problem of fitting atmospheric dispersion parameters based on time-resolved back-scattered differential absorption Lidar (DIAL) measurements. The obvious advantage of light-based remote sensing modalities is their extended spa
Externí odkaz:
http://arxiv.org/abs/2304.06225
Autor:
Lu, Yuhong, Polydorides, Nicholas
This thesis analyzes the challenging problem of Image Deblurring based on classical theorems and state-of-art methods proposed in recent years. By spectral analysis we mathematically show the effective of spectral regularization methods, and point ou
Externí odkaz:
http://arxiv.org/abs/2208.11622
Publikováno v:
IEEE Access, Vol 12, Pp 6400-6412 (2024)
In recent years, considerable effort has been directed towards non-contact Wi-Fi sensing applications such as fall detection and vital sign monitoring. For emerging technologies in healthcare, it is essential to assess the validity and repeatability
Externí odkaz:
https://doaj.org/article/af6425956d774801bfa35efac1f160c1
Autor:
Liao, Xiaoyan, Schmidt, Alicia L., Zhang, Dongwei, Li, Peizi, Wang, Xintong, Ko, Huaibin M., Choi, Won-Tak, Alpert, Lindsay, Hao, Yansheng, Kovar-Peltz, Sierra, Polydorides, Alexandros D., Wanjari, Pankhuri, Mastro, Julius, Wang, Peng
Publikováno v:
In Modern Pathology October 2024 37(10)
Autor:
Wong, Serre-Yu, Rowan, Cathy, Brockmans, Elvira Diaz, Law, Cindy C.Y., Giselbrecht, Elisabeth, Ang, Celina, Khaitov, Sergey, Sachar, David, Polydorides, Alexandros D., Winata, Leon Shin-han, Verstockt, Bram, Spinelli, Antonino, Rubin, David T., Deepak, Parakkal, McGovern, Dermot P.B., McDonald, Benjamin D., Lung, Phillip, Lundby, Lilli, Lightner, Amy L., Holubar, Stefan D., Hanna, Luke, Hamarth, Carla, Geldof, Jeroen, Dige, Anders, Cohen, Benjamin L., Carvello, Michele, Bonifacio, Cristiana, Bislenghi, Gabriele, Behrenbruch, Corina, Ballard, David H., Altinmakas, Emre, Sebastian, Shaji, Tozer, Phil, Hart, Ailsa, Colombel, Jean-Frederic
Publikováno v:
In Clinical Gastroenterology and Hepatology
Spectral Photon-Counting Computed Tomography (SPCCT) is a promising technology that has shown a number of advantages over conventional X-ray Computed Tomography (CT) in the form of material separation, artefact removal and enhanced image quality. How
Externí odkaz:
http://arxiv.org/abs/2003.04138
Autor:
Matthew Brown, Nina Bhardwaj, Cansu Cimen Bozkus, Aimee L Lucas, Alexandros D Polydorides, Leandra Velazquez, Mesude Bicak, Juhana Habib, Sharonne Holtzman, Mona Saleh, Robert Samstein
Publikováno v:
Journal for ImmunoTherapy of Cancer, Vol 11, Iss Suppl 1 (2023)
Externí odkaz:
https://doaj.org/article/5e8efdbf4f6643c9a5698a410d60bd9c