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pro vyhledávání: '">MD"'
Skin cancer is a serious and potentially fatal disease caused by DNA damage. Early detection significantly increases survival rates, making accurate diagnosis crucial. In this groundbreaking study, we present a hybrid framework based on Deep Learning
Externí odkaz:
http://arxiv.org/abs/2410.14489
Autor:
Khatun, Rabea, Tasnim, Wahia, Akter, Maksuda, Islam, Md Manowarul, Uddin, Md. Ashraf, Mahmud, Md. Zulfiker, Das, Saurav Chandra
Gallbladder cancer (GBC) is the most frequent cause of disease among biliary tract neoplasms. Identifying the molecular mechanisms and biomarkers linked to GBC progression has been a significant challenge in scientific research. Few recent studies ha
Externí odkaz:
http://arxiv.org/abs/2410.14433
Autor:
Haider, Fabiha, Shifat, Fariha Tanjim, Ishmam, Md Farhan, Barua, Deeparghya Dutta, Sourove, Md Sakib Ul Rahman, Fahim, Md, Alam, Md Farhad
The proliferation of transliterated texts in digital spaces has emphasized the need for detecting and classifying hate speech in languages beyond English, particularly in low-resource languages. As online discourse can perpetuate discrimination based
Externí odkaz:
http://arxiv.org/abs/2410.13281
Autor:
Kowsher, Md, Sobuj, Md. Shohanur Islam, Prottasha, Nusrat Jahan, Alanis, E. Alejandro, Garibay, Ozlem Ozmen, Yousefi, Niloofar
Time series forecasting remains a challenging task, particularly in the context of complex multiscale temporal patterns. This study presents LLM-Mixer, a framework that improves forecasting accuracy through the combination of multiscale time-series d
Externí odkaz:
http://arxiv.org/abs/2410.11674
Autor:
Prottasha, Nusrat Jahan, Mahmud, Asif, Sobuj, Md. Shohanur Islam, Bhat, Prakash, Kowsher, Md, Yousefi, Niloofar, Garibay, Ozlem Ozmen
Large Language Models (LLMs) are gaining significant popularity in recent years for specialized tasks using prompts due to their low computational cost. Standard methods like prefix tuning utilize special, modifiable tokens that lack semantic meaning
Externí odkaz:
http://arxiv.org/abs/2410.08598
Heart failure remains a major global health challenge, contributing significantly to the 17.8 million annual deaths from cardiovascular disease, highlighting the need for improved diagnostic tools. Current heart disease prediction models based on cla
Externí odkaz:
http://arxiv.org/abs/2410.07446
Autor:
Hasan, Md. Tarek, Shamael, Mohammad Nazmush, Billah, H. M. Mutasim, Akter, Arifa, Hossain, Md Al Emran, Islam, Sumayra, Islam, Salekul, Shatabda, Swakkhar
Peer review is the quality assessment of a manuscript by one or more peer experts. Papers are submitted by the authors to scientific venues, and these papers must be reviewed by peers or other authors. The meta-reviewers then gather the peer reviews,
Externí odkaz:
http://arxiv.org/abs/2410.04202
Autor:
Islam, Shayekh Bin, Rahman, Md Asib, Hossain, K S M Tozammel, Hoque, Enamul, Joty, Shafiq, Parvez, Md Rizwan
Retrieval-Augmented Generation (RAG) has been shown to enhance the factual accuracy of Large Language Models (LLMs), but existing methods often suffer from limited reasoning capabilities in effectively using the retrieved evidence, particularly when
Externí odkaz:
http://arxiv.org/abs/2410.01782
Let $\mathcal{S}^*(\varphi)$ be the class of all analytic functions $f$ in the unit disk $\mathbb{D}=\{z\in\mathbb{C}:|z|<1\}$, normalized by $f(0)=f'(0)-1=0$ that satisfy the subordination relation $zf'(z)/f(z)\prec\varphi(z)$, where $\varphi$ is an
Externí odkaz:
http://arxiv.org/abs/2409.20216