Results 71 to 80 of about 11,306 (258)
New Directions for Adult and Continuing Education, EarlyView.ABSTRACT Advancing artificial intelligence (AI) has transformed learning and work, yet higher education and professional development programs have not systematically equipped learners for AI‐prevalent environments. This lack of preparation creates uncertainty regarding control, responsibility, trust, and accountability.
Moon‐Heum Cho, Jerusalem Merkebu
wiley +1 more source
An Experimental Analysis of Deep Neural Network Based Classifiers for Sentiment Analysis Task
IEEE Access, 2023 The application of natural language processing (NLP) in sentiment analysis task by using textual data has wide scale application across various domains in plethora of industries.
Mrigank Shukla, Akhil Kumar
doaj +1 more source
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Background Cognitive impairment is a common non‐motor symptom in Multiple Sclerosis (MS), negatively affecting autonomy and Quality of Life (QoL). Innovative rehabilitation strategies, such as semi‐immersive virtual reality (VR) and computerized cognitive training (CCT), may offer advantages over traditional cognitive rehabilitation (TCR ...
Maria Grazia Maggio +8 more
wiley +1 more source
Arthritis Care &Research, EarlyView.Objective To support high‐quality, patient‐centered care for systemic lupus erythematosus (SLE), the American College of Rheumatology (ACR) developed evidence‐based measures incorporating clinical and patient‐reported outcome measures (PROMs). Using the Consolidated Framework for Implementation Research (CFIR), we conducted semistructured interviews ...
Catherine Nasrallah +13 more
wiley +1 more source
Better Word Representation Vectors Using Syllabic Alphabet: A Case Study of Swahili
Applied Sciences, 2019 Deep learning has extensively been used in natural language processing with sub-word representation vectors playing a critical role. However, this cannot be said of Swahili, which is a low resource and widely spoken language in East and Central Africa ...
Casper S. Shikali +3 more
doaj +1 more source
Deconstructing Word Embeddings
CoRR, 2019 A review of Word Embedding Models through a deconstructive approach reveals their several shortcomings and inconsistencies. These include instability of the vector representations, a distorted analogical reasoning, geometric incompatibility with linguistic features, and the inconsistencies in the corpus data.
openaire +2 more sources
All Word Embeddings from One Embedding
CoRR, 2020 NeurIPS ...
Sho Takase, Sosuke Kobayashi
openaire +3 more sources
Arthritis Care &Research, EarlyView.Objective To evaluate utility of an artificial intelligence (AI) health coach for systemic sclerosis (SSc) self‐management and identify patterns associated with participant engagement. Methods We conducted a mixed methods study in which an AI health coach, powered by a large language model (LLM), was used to support self‐management for SSc.
Nirali Shah +4 more
wiley +1 more source
What Do Large Language Models Know About Materials?
Advanced Engineering Materials, EarlyView.If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer +2 more
wiley +1 more source
Predicting High-Level Human Judgment Across Diverse Behavioral Domains
Collabra: Psychology, 2019 Recent advances in machine learning, combined with the increased availability of large natural language datasets, have made it possible to uncover semantic representations that characterize what people know about and associate with a wide range of ...
Russell Richie +2 more
doaj +1 more source