Zobrazeno 1 - 10
of 4 299
pro vyhledávání: '"Arnaout, A."'
In deep learning, achieving high performance on image classification tasks requires diverse training sets. However, the current best practice$\unicode{x2013}$maximizing dataset size and class balance$\unicode{x2013}$does not guarantee dataset diversi
Externí odkaz:
http://arxiv.org/abs/2407.15724
Autor:
Miao, Brenda Y., Chen, Irene Y., Williams, Christopher YK, Davidson, Jaysón, Garcia-Agundez, Augusto, Sun, Shenghuan, Zack, Travis, Saria, Suchi, Arnaout, Rima, Quer, Giorgio, Sadaei, Hossein J., Torkamani, Ali, Beaulieu-Jones, Brett, Yu, Bin, Gianfrancesco, Milena, Butte, Atul J., Norgeot, Beau, Sushil, Madhumita
Recent advances in generative models, including large language models (LLMs), vision language models (VLMs), and diffusion models, have accelerated the field of natural language and image processing in medicine and marked a significant paradigm shift
Externí odkaz:
http://arxiv.org/abs/2403.02558
Autor:
Nguyen, Phuc, Arora, Rohit, Hill, Elliot D., Braun, Jasper, Morgan, Alexandra, Quintana, Liza M., Mazzoni, Gabrielle, Lee, Ghee Rye, Arnaout, Rima, Arnaout, Ramy
Machine-learning datasets are typically characterized by measuring their size and class balance. However, there exists a richer and potentially more useful set of measures, termed diversity measures, that incorporate elements' frequencies and between
Externí odkaz:
http://arxiv.org/abs/2401.00102
Autor:
Couch, Josiah, Arora, Rohit, Braun, Jasper, Kaplinsky, Joesph, Hill, Elliot, Li, Anthony, Altschul, Brett, Arnaout, Ramy
Previously, it has been shown that maximum-entropy models of immune-repertoire sequence can be used to determine a person's vaccination status. However, this approach has the drawback of requiring a computationally intensive method to compute each mo
Externí odkaz:
http://arxiv.org/abs/2312.12525
Autor:
Ferreira, Danielle, Arnaout, Rima
Foundation models are experiencing a surge in popularity. The Segment Anything model (SAM) asserts an ability to segment a wide spectrum of objects but required supervised training at unprecedented scale. We compared SAM's performance (against clinic
Externí odkaz:
http://arxiv.org/abs/2311.04847
Publikováno v:
Egyptian Journal of Neurosurgery, Vol 39, Iss 1, Pp 1-11 (2024)
Abstract Metastases in the brain are a devastating and common cancer with a poor prognosis. Physicians, on the other hand, may help their patients by suspecting, recognizing, and treating them correctly. It is predicted that between 8 and 10% of canc
Externí odkaz:
https://doaj.org/article/dcd612bfdc4d4302af5a0281707b65d8
Autor:
Kevin T. Huang, Jack McNulty, Helweh Hussein, Neil Klinger, Melissa M. J. Chua, Patrick R. Ng, Joshua Chalif, Neel H. Mehta, Omar Arnaout
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-8 (2024)
Abstract While ventricular shunts are the main treatment for adult hydrocephalus, shunt malfunction remains a common problem that can be challenging to diagnose. Computer vision-derived algorithms present a potential solution. We designed a feasibili
Externí odkaz:
https://doaj.org/article/7d9bff640da54ce0bd402dbef9247b75
Autor:
Muhamad Zakaria Brimo Alsaman, Fares Abu Sultan, Yazan Ramadan, Khaled Arnaout, Mohamad Shahrour, Bilal Barakat, Abeer Dayeh
Publikováno v:
Journal of Medical Case Reports, Vol 18, Iss 1, Pp 1-4 (2024)
Abstract Introduction Hemophagocytic lymphohistiocytosis characterized by hemophagocytosis leading to uncontrolled inflammation; the most common etiology in secondary cases of hemophagocytic lymphohistiocytosis is viral infections, especially Epstein
Externí odkaz:
https://doaj.org/article/dccaa011dc5647d9b1472515ec33d4d5
Autor:
Arnaout, Hiba, Razniewski, Simon
We examine the ability of large language models (LLMs) to generate salient (interesting) negative statements about real-world entities; an emerging research topic of the last few years. We probe the LLMs using zero- and k-shot unconstrained probes, a
Externí odkaz:
http://arxiv.org/abs/2305.16755
Publikováno v:
Under review, 2022
General-purpose knowledge bases (KBs) are a cornerstone of knowledge-centric AI. Many of them are constructed pragmatically from Web sources, and are thus far from complete. This poses challenges for the consumption as well as the curation of their c
Externí odkaz:
http://arxiv.org/abs/2305.05403