Results 131 to 140 of about 23,764 (310)

Pathways and pitfalls: a qualitative study of student experiences in biomedical science education

FEBS Open Bio, EarlyView.
Biomedical science students from underrepresented backgrounds face barriers including financial strain, disrupted laboratory access and cultural exclusion. Peer networks provide vital support when institutional systems are difficult to navigate. To create inclusive learning environments and achieve academic success, educators should blend active, hands‐
Olivia J. Russell, Cassy Ross, Panagiota S. Filippou, Bruno Silvester Lopes, Dominic Gilchrist, Paul Dean, Kamar Ameen‐Ali, Tora K. Smulders‐Srinivasan, Ahmad A. Khundakar   +8 more
wiley   +1 more source

Moviereco: A Recommendation System

, 2007
{"references": ["Konstan J A, Miller B N, Maltz D, Herlocked J L, Gordon L R and Riedl\nJ GroupLens : Applying Collaborative Filtering to Usenet News\nCommunication ACM 40, 3 (page 77-87)", "Konstan J A, Reidl J, Explaining Collaborative Filtering\nReommendation ACM 2000 Conference on Computer Supported\nCollaborative Work.", "H. Herlocker J, Konstan J
Dipankaj G. Medhi, Juri Dakua
openaire   +2 more sources

A new flow chip in combination with multiphoton microscopy as a protocol for longitudinal 3D imaging of tissue calcification under shear stress

FEBS Open Bio, EarlyView.
Miniaturized flow chip platform enabling continuous perfusion and longitudinal multiphoton 3D imaging of vascular smooth muscle cell constructs under physiological flow. Brightfield imaging guides region selection, while CellTracker Green and mRuby‐labeled fetuin‐A visualize cells and mineral deposition, respectively. Magnesium supplementation markedly
Vytautas Kučikas, Aaron D. Morgan, Ignas Čiurlionis, Christian Böhm, Stefan Jockenhövel, Willi Jahnen‐Dechent, Marc A. M. J. van Zandvoort   +6 more
wiley   +1 more source

Continual Recommender Systems

Proceedings of the 34th ACM International Conference on Information and Knowledge Management
Modern recommender systems operate in uniquely dynamic settings: user interests, item pools, and popularity trends shift continuously, and models must adapt in real time without forgetting past preferences. While existing tutorials on continual or lifelong learning cover broad machine learning domains (e.g., vision and graphs), they do not address ...
Hyunsik Yoo, Seongku Kang, Hanghang Tong
openaire   +2 more sources

Capturing Interest Through Inference and Visualization: Ontological User Profiling in Recommender Systems

, 2003
Tools for filtering the World Wide Web exist, but they are hampered by the difficulty of capturing user preferences in such a diverse and dynamic environment.
De Roure, D.C., Middleton, Stuart, Shadbolt, N.R.   +2 more
core  

EMERS: Energy Meter for Recommender Systems

Due to recent advancements in machine learning, recommender systems use increasingly more energy for training, evaluation, and deployment. However, the recommender systems community often does not report the energy consumption of their experiments.
Beel, Joeran, Said, Alan,, Wegmeth, Lukas, Vente, Tobias   +3 more
core   +1 more source

Mining Contextual Knowledge for Context-Aware Recommender Systems

, 2012
With the rapid growth of the number of electronic transactions conducted over the Internet, recommender systems have been proposed to provide consumers with personalized product recommendations. A hybrid symbolic and quantitative approach for recommender
Lau, Raymond, Raymond Lau, Zhang, Wenping, Wenping Zhang, Tao, Xiaohui, Xiaohui Tao   +5 more
core   +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

KT-CDULF: Knowledge Transfer in Context-Aware Cross-Domain Recommender Systems via Latent User Profiling

IEEE Access
Recommender systems are crucial in today’s digital world, by enhancing user engagement experience in digital ecosystems. Internet of things (IoT) have huge potential to generate dynamic and real time data.
Adeel Ashraf Cheema, Muhammad Shahzad Sarfraz, Muhammad Usman, Qamar Uz Zaman, Usman Habib, Ekkarat Boonchieng   +5 more
doaj   +1 more source

Intelligent Tutoring Systems for Adult Learning in STEM Disciplines

New Directions for Adult and Continuing Education, EarlyView.
ABSTRACT Intelligent tutoring systems (ITS) are reshaping adult learning in STEM by providing adaptive, data‐driven instruction across classrooms, workplaces, and informal environments. In the context of ITS, this article compares generative AI, which creates personalized explanations and practice materials, with explainable AI, which focuses on ...
Jill Zarestky, Amanda R. Lager Gleason
wiley   +1 more source