Results 71 to 80 of about 972,067 (310)

Interrogating the immune landscape of microsatellite stable RAS‐mutated colon cancer

Molecular Oncology, EarlyView.
COLOSSUS project RAS‐mutated MSS colon cancer study explored transcriptomics and immune cell density by immunohistochemistry (IHC), Immunoscore (IS), ISIC/TuLIS scores, mutation counts, and detected different prevalences but similar microenvironment composition across immune markers with clinical relevance for future immunotherapy combination ...
Rodrigo Dienstmann, Eduardo García‐Galea, Alice O'Farrell, Zak Kinsella, Maxime Meylan, Florent Petitprez, Ingrid Arijs, Tom Venken, Hari Ps, Adrian Lärkeryd, Ian Miller, Janick Selves, Nadja Meindl‐Beinker, Fiorella Ruiz‐Pace, Elena Élez, Raquel Comas‐Navarro, Frank Lincoln, Dirk Fey, Gift Nyamundanda, Aoife Nolan, Joern Lewin, Raquel Perez‐Lopez, Jonathan Briody, Kathleen Bennett, Walter Kolch, David Matallanas, Alexander Kel, Enrique Arenas, Joaquín Arribas, Bart Ghesquière, Josep Tabernero, Julie Meilleroux, Deborah McNamara, Ray McDermott, Marvin Lim, Mary O'Reilly, Brian Bird, Lisa Stack, Lucia Moloney, Patrick Morris, Keith Egan, Maciej Milewski, Lars Scheuer, Joachim Behringer, Georg Bolz, Ramon Salazar, Cristina Santos, Andrea Ruiz, Orla Casey, Verena Murphy, Matthias Ebert, Livio Trusolino, Diether Lambrechts, Anguraj Sadanandam, Catherine Sautès‐Fridman, Jochen Prehn, Paolo Nuciforo, Jacques Fieschi, Florence Monville, Darran O'Connor, Wolf Fridman, Annette Byrne   +61 more
wiley   +1 more source

Machine Translation in Low-Resource Languages by an Adversarial Neural Network

Applied Sciences, 2021
Existing Sequence-to-Sequence (Seq2Seq) Neural Machine Translation (NMT) shows strong capability with High-Resource Languages (HRLs). However, this approach poses serious challenges when processing Low-Resource Languages (LRLs), because the model ...
Mengtao Sun, Hao Wang, Mark Pasquine, Ibrahim A. Hameed   +3 more
doaj   +1 more source

A Survey on Challenges and Advances in Natural Language Processing with a Focus on Legal Informatics and Low-Resource Languages

Electronics
The field of Natural Language Processing (NLP) has experienced significant growth in recent years, largely due to advancements in Deep Learning technology and especially Large Language Models.
Panteleimon Krasadakis, E. Sakkopoulos, V. Verykios   +2 more
semanticscholar   +1 more source

Universal Neural Machine Translation for Extremely Low Resource Languages [PDF]

North American Chapter of the Association for Computational Linguistics, 2018
In this paper, we propose a new universal machine translation approach focusing on languages with a limited amount of parallel data. Our proposed approach utilizes a transfer-learning approach to share lexical and sentence level representations across ...
Jiatao Gu, Hany Hassan, Jacob Devlin, V. Li   +3 more
semanticscholar   +1 more source

Dense Retrieval for Low Resource languages - the Case of Amharic Language

Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval
4 pages, 2 ...
Tilahun Yeshambel, Moncef Garouani, Serge Molina, Josiane Mothe   +3 more
openaire   +2 more sources

Establishing an assay to evaluate d‐amino acid oxidase enzyme kinetics and inhibition using WST‐8 redox dye

FEBS Open Bio, EarlyView.
This study investigated a novel WST‐8‐based assay for evaluating d‐Amino acid oxidase (DAO) inhibitors. We confirmed its effectiveness using known inhibitors and found that uremic toxins possess relatively weak inhibitory activity compared to existing drugs.
Kahoko Miyake, Yuki Enoki, Yuka Nakazawa, Kazuaki Taguchi, Kazuaki Matsumoto   +4 more
wiley   +1 more source

CINOSUM:An Extractive Summarization Model for Low-resource Multi-ethnic Language [PDF]

Jisuanji kexue
To address the issue of existing models being unable to handle abstractive summarization for low-resource multilingual languages,this paper proposes an extractive summarization model,CINOSUM,based on CINO(a Chinese minority pre-trained language model).We
WENG Yu, LUO Haoyu, Chaomurilige, LIU Xuan , DONG Jun, LIU Zheng
doaj   +1 more source

Lesan -- Machine Translation for Low Resource Languages

CoRR, 2021
Millions of people around the world can not access content on the Web because most of the content is not readily available in their language. Machine translation (MT) systems have the potential to change this for many languages. Current MT systems provide very accurate results for high resource language pairs, e.g., German and English.
Asmelash Teka Hadgu, Abel Aregawi, Adam Beaudoin   +2 more
openaire   +3 more sources

Digital twins to accelerate target identification and drug development for immune‐mediated disorders

FEBS Open Bio, EarlyView.
Digital twins integrate patient‐derived molecular and clinical data into personalised computational models that simulate disease mechanisms. They enable rapid identification and validation of therapeutic targets, prediction of drug responses, and prioritisation of candidate interventions.
Anna Niarakis, Philippe Moingeon
wiley   +1 more source

Risk Prediction Models for Recurrence After Curative Treatment of Early‐Stage or Locally Advanced Lung Cancer: A Systematic Review

Aging and Cancer, EarlyView.
This systematic review synthesizes prognostic models for survival and recurrence in resected non‐small cell lung cancer. While many models demonstrate moderate to good discrimination, few are externally validated and reporting quality is variable, limiting clinical applicability and highlighting the need for robust, transparent model development ...
Evangeline Samuel, S. Tissera, E. Paul, J. Zalcberg, R. G. Stirling   +4 more
wiley   +1 more source