Zobrazeno 1 - 10
of 6 873
pro vyhledávání: '"A Wistuba"'
Autor:
Schneider, Lennart, Wistuba, Martin, Klein, Aaron, Golebiowski, Jacek, Zappella, Giovanni, Merra, Felice Antonio
Optimal prompt selection is crucial for maximizing large language model (LLM) performance on downstream tasks. As the most powerful models are proprietary and can only be invoked via an API, users often manually refine prompts in a black-box setting
Externí odkaz:
http://arxiv.org/abs/2412.07820
Recent Continual Learning (CL) methods have combined pretrained Transformers with prompt tuning, a parameter-efficient fine-tuning (PEFT) technique. We argue that the choice of prompt tuning in prior works was an undefended and unablated decision, wh
Externí odkaz:
http://arxiv.org/abs/2406.03216
Autor:
Alejandra G. Serrano, Pedro Rocha, Cibelle Freitas Lima, Allison Stewart, Bingnan Zhang, Lixia Diao, Junya Fujimoto, Robert J. Cardnell, Wei Lu, Khaja Khan, Beate Sable, Aaron R. Ellison, Ignacio I. Wistuba, Kyle F. Concannon, Daniel M. Halperin, Czerniak Bogdan, Kanishka Sircar, Miao Zhang, Kasey Cargill, Qi Wang, Ana Aparicio, Alexander Lazar, Sharia Hernandez, Jeannelyn Estrella, Preetha Ramalingam, Adel El-Naggar, Neda Kalhor, Carl M. Gay, Lauren Averett Byers, Luisa M. Solis Soto
Publikováno v:
npj Precision Oncology, Vol 8, Iss 1, Pp 1-13 (2024)
Abstract Delta-like Ligand 3 (DLL3) targeting therapies are promising in small cell lung cancer (SCLC) treatment. However, DLL3 expression in SCLC and other neuroendocrine neoplasms (NEN) is heterogeneous and not well characterized. We describe the l
Externí odkaz:
https://doaj.org/article/ff8fbd20faf44861bff7caa2e497764c
Autor:
Simone Anfossi, Faezeh Darbaniyan, Joseph Quinlan, Steliana Calin, Masayoshi Shimizu, Meng Chen, Paola Rausseo, Michael Winters, Elena Bogatenkova, Kim-Anh Do, Ivan Martinez, Ziyi Li, Loredana Antal, Tudor Rares Olariu, Ignacio Wistuba, George A. Calin
Publikováno v:
Molecular Cancer, Vol 23, Iss 1, Pp 1-17 (2024)
Abstract Background Cancer patients are more susceptible to an aggressive course of COVID-19. Developing biomarkers identifying cancer patients at high risk of COVID-19-related death could help determine who needs early clinical intervention. The miR
Externí odkaz:
https://doaj.org/article/6fe26fed80f541c6b9db9eafb0c7839c
Autor:
Chenyang Li, Thinh T. Nguyen, Jian-Rong Li, Xingzhi Song, Junya Fujimoto, Latasha Little, Curtis Gumb, Chi-Wan B. Chow, Ignacio I. Wistuba, Andrew P. Futreal, Jianhua Zhang, Shawna M. Hubert, John V. Heymach, Jia Wu, Christopher I. Amos, Jianjun Zhang, Chao Cheng
Publikováno v:
npj Precision Oncology, Vol 8, Iss 1, Pp 1-14 (2024)
Abstract Lung Cancer remains the leading cause of cancer deaths in the USA and worldwide. Non-small cell lung cancer (NSCLC) harbors high transcriptomic intratumor heterogeneity (RNA-ITH) that limits the reproducibility of expression-based prognostic
Externí odkaz:
https://doaj.org/article/b6fe0a65261748579d8ae587987a1d01
Continual learning enables the incremental training of machine learning models on non-stationary data streams.While academic interest in the topic is high, there is little indication of the use of state-of-the-art continual learning algorithms in pra
Externí odkaz:
http://arxiv.org/abs/2304.12067
Gradient boosting machines (GBMs) based on decision trees consistently demonstrate state-of-the-art results on regression and classification tasks with tabular data, often outperforming deep neural networks. However, these models do not provide well-
Externí odkaz:
http://arxiv.org/abs/2302.10706
Hyperparameter optimization is an important subfield of machine learning that focuses on tuning the hyperparameters of a chosen algorithm to achieve peak performance. Recently, there has been a stream of methods that tackle the issue of hyperparamete
Externí odkaz:
http://arxiv.org/abs/2302.00441
Autor:
José L. Solórzano, Victoria Menéndez, Edwin Parra, Luisa Solis, Ruth Salazar, Mónica García-Cosío, Fina Climent, Sara Fernández, Eva Díaz, Alejandro Francisco-Cruz, Joseph Khoury, Mei Jiang, Auriole Tamegnon, Carlos Montalbán, Ignacio Melero, Ignacio Wistuba, Carlos De Andrea, Juan F. García
Publikováno v:
OncoImmunology, Vol 13, Iss 1 (2024)
The Hodgkin and Reed – Sternberg (HRS) cells in classical Hodgkin Lymphoma (cHL) actively modify the immune tumor microenvironment (TME) attracting immunosuppressive cells and expressing inhibitory molecules. A high frequency of myeloid cells in th
Externí odkaz:
https://doaj.org/article/eca23b7e29a44b36a41152a418b1a45b
Autor:
Ditz, Jonas Christian, Wistuba-Hamprecht, Jacqueline, Maier, Timo, Fendel, Rolf, Pfeifer, Nico, Reuter, Bernhard
Motivation: Machine learning methods can be used to support scientific discovery in healthcare-related research fields. However, these methods can only be reliably used if they can be trained on high-quality and curated datasets. Currently, no such d
Externí odkaz:
http://arxiv.org/abs/2301.06454