45   Artículos

 
en línea
Seokjoon Kwon, Jae-Hyeon Park, Hee-Deok Jang, Hyunwoo Nam and Dong Eui Chang    
Deep learning algorithms are widely used for pattern recognition in electronic noses, which are sensor arrays for gas mixtures. One of the challenges of using electronic noses is sensor drift, which can degrade the accuracy of the system over time, even ... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Rejath Jose, Faiz Syed, Anvin Thomas and Milan Toma    
The advancement of machine learning in healthcare offers significant potential for enhancing disease prediction and management. This study harnesses the PyCaret library?a Python-based machine learning toolkit?to construct and refine predictive models for... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Nirmal Acharya, Padmaja Kar, Mustafa Ally and Jeffrey Soar    
Significant clinical overlap exists between mental health and substance use disorders, especially among women. The purpose of this research is to leverage an AutoML (Automated Machine Learning) interface to predict and distinguish co-occurring mental hea... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Leon Kopitar, Iztok Fister, Jr. and Gregor Stiglic    
Introduction: Type 2 diabetes mellitus is a major global health concern, but interpreting machine learning models for diagnosis remains challenging. This study investigates combining association rule mining with advanced natural language processing to im... ver más
Revista: Information    Formato: Electrónico

 
en línea
Weiwei Yuan, Wanxia Yang, Liang He, Tingwei Zhang, Yan Hao, Jing Lu and Wenbo Yan    
The extraction of entities and relationships is a crucial task in the field of natural language processing (NLP). However, existing models for this task often rely heavily on a substantial amount of labeled data, which not only consumes time and labor bu... ver más
Revista: Agriculture    Formato: Electrónico

 
en línea
Tingkai Hu, Zuqin Chen, Jike Ge, Zhaoxu Yang and Jichao Xu    
Insufficiently labeled samples and low-generalization performance have become significant natural language processing problems, drawing significant concern for few-shot text classification (FSTC). Advances in prompt learning have significantly improved t... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Qiang He, Guowei Chen, Wenchao Song and Pengzhou Zhang    
Named entity recognition (NER) is a subfield of natural language processing (NLP) that identifies and classifies entities from plain text, such as people, organizations, locations, and other types. NER is a fundamental task in information extraction, inf... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Feiyang Ye, Liang Huang, Senjie Liang and KaiKai Chi    
Named entity recognition (NER) in a few-shot setting is an extremely challenging task, and most existing methods fail to account for the gap between NER tasks and pre-trained language models. Although prompt learning has been successfully applied in few-... ver más
Revista: Information    Formato: Electrónico

 
en línea
Hana Alostad, Shoug Dawiek and Hasan Davulcu    
The Kuwaiti dialect is a particular dialect of Arabic spoken in Kuwait; it differs significantly from standard Arabic and the dialects of neighboring countries in the same region. Few research papers with a focus on the Kuwaiti dialect have been publishe... ver más
Revista: Big Data and Cognitive Computing    Formato: Electrónico

 
en línea
Md. Jamal Uddin, Md. Martuza Ahamad, Md. Nesarul Hoque, Md. Abul Ala Walid, Sakifa Aktar, Naif Alotaibi, Salem A. Alyami, Muhammad Ashad Kabir and Mohammad Ali Moni    
Diabetes is a chronic disease caused by a persistently high blood sugar level, causing other chronic diseases, including cardiovascular, kidney, eye, and nerve damage. Prompt detection plays a vital role in reducing the risk and severity associated with ... ver más
Revista: Information    Formato: Electrónico

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