Results 51 to 60 of about 2,544,926 (320)
Decrypting cancer's spatial code: from single cells to tissue niches
Molecular Oncology, EarlyView.Spatial transcriptomics maps gene activity across tissues, offering powerful insights into how cancer cells are organised, switch states and interact with their surroundings. This review outlines emerging computational, artificial intelligence (AI) and geospatial approaches to define cell states, uncover tumour niches and integrate spatial data with ...
Cenk Celik +4 more
wiley +1 more source
Characterizing Phishing Threats with Natural Language Processing
, 2015 Spear phishing is a widespread concern in the modern network security landscape, but there are few metrics that measure the extent to which reconnaissance is performed on phishing targets.
Kotson, Michael C., Schulz, Alexia
core +1 more source
Natural language understanding: instructions for (Present and Future) use [PDF]
, 2018 In this paper I look at Natural Language Understanding, an area of Natural Language Processing aimed at making sense of text, through the lens of a visionary future: what do we expect a machine should be able to understand?
Navigli, R.
core +1 more source
Brains and algorithms partially converge in natural language processing
Communications Biology, 2022 Deep learning algorithms trained to predict masked words from large amount of text have recently been shown to generate activations similar to those of the human brain. However, what drives this similarity remains currently unknown.
C. Caucheteux, J. King
semanticscholar +1 more source
Report on the 2nd MObility for Vesicle research in Europe (MOVE) symposium—2024
FEBS Open Bio, EarlyView.The 2nd MObility for Vesicle research in Europe (MOVE) Symposium in Belgrade brought over 280 attendees from 28 countries to advance extracellular vesicle (EV) research. Featuring keynotes, presentations, and industry sessions, it covered EV biogenesis, biomarkers, therapies, and manufacturing.
Dorival Mendes Rodrigues‐Junior +5 more
wiley +1 more source
Quantifying Uncertainties in Natural Language Processing Tasks
, 2018 Reliable uncertainty quantification is a first step towards building explainable, transparent, and accountable artificial intelligent systems. Recent progress in Bayesian deep learning has made such quantification realizable.
Wang, William Yang, Xiao, Yijun
core +1 more source
Natural language processing: state of the art, current trends and challenges [PDF]
Multimedia tools and applications, 2017 Natural language processing (NLP) has recently gained much attention for representing and analyzing human language computationally. It has spread its applications in various fields such as machine translation, email spam detection, information extraction,
Diksha Khurana +3 more
semanticscholar +1 more source
New Directions for Adult and Continuing Education, EarlyView.ABSTRACT This autobiographical article recounts a White woman's efforts to establish a center for teaching and learning (CTL) in a large HBCU in the southern part of the United States. She describes the ways in which tenets of critical feminism, feminist pedagogies, and adult learning and development informed her approach to faculty development.
Audrey Dentith
wiley +1 more source
Text content and task performance in the evaluation of a natural language generation system [PDF]
, 2009 An important question in the evaluation of Natural Language Generation systems concerns the relationship between textual characteristics and task performance.
Gatt, Albert +2 more
core
SKOPE: A connectionist/symbolic architecture of spoken Korean processing
, 1995 Spoken language processing requires speech and natural language integration. Moreover, spoken Korean calls for unique processing methodology due to its linguistic characteristics.
Lee, Geunbae, Lee, Jong-Hyeok
core +1 more source