The interaction network and potential clinical effectiveness of dimensional psychopathology phenotyping based on EMR: a Bayesian network approach by Jianqing Qiu, Ting Zhu, Ke Qin, Wei Zhang

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Organizing an in-class hackathon to correct PDF-to-text conversion errors of 1.0 by Sunho Kim, Royoung Kim, Hee-Jo Nam, Ryeo-Gyeong Kim, Enjin Ko, Han-Su Kim, Jihye Shin, Daeun Cho, Yurhee Jin, Soyeon Bae, Ye Won Jo, San Ah Jeong, Yena Kim, Seoyeon Ahn, Bomi Jang, Jiheyon Seong, Yujin Lee, Si Eun Seo, Yujin Kim, Ha-Jeong Kim, Hyeji Kim, Hye-Lynn Sung, Hyoyoung Lho, Jaywon Koo, Jion Chu, Juwon Lim, Youngju Kim, Kyungyeon Lee, Yuri Lim, Meongeun Kim, Seonjeong Hwang, Shinhye Han, Sohyeun Bae, Sua Kim, Suhyeon Yoo, Yeonjeong Seo, Yerim Shin, Yonsoo Kim, You-Jung Ko, Jihee Baek, Hyejin Hyun, Hyemin Choi, Ji-Hye Oh, Da-Young Kim, Hyun-Seok Park

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Unsupervised Quality Estimation Model for English to German Translation and Its Application in Extensive Supervised Evaluation by Aaron L.-F. Han, Derek F. Wong, Lidia S. Chao, Liangye He, Yi Lu

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A Systematic Comparison of Data Selection Criteria for SMT Domain Adaptation by Longyue Wang, Derek F. Wong, Lidia S. Chao, Yi Lu, Junwen Xing

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Clinical Applications of Machine Learning by Nadayca Mateussi, PhD, Michael P. Rogers, MD, Emily A. Grimsley, MD, Meagan Read, MD, Rajavi Parikh, DO, Ricardo Pietrobon, MD, PhD, Paul C. Kuo, MD

“…This review introduces interpretable predictive machine learning approaches, natural language processing, image recognition, and reinforcement learning methodologies to familiarize end users. …”
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Expletive ta in Mandarin Chinese: A Quantitative Study by Yue Yu, Qiurong Zhao

“…The findings not only provide evidence to show that even in radical pro-drop languages such as Mandarin, pleonastics can occur in both object and subject positions but also offer important insights for Chinese natural language processing.…”
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Survey of text classification methods based on deep learning by Sijia DU, Haining YU, Hongli ZHANG

“…Text classification is a research hot spot in the field of natural language processing,which is mainly used in public opinion detection,news classification and other fields.In recent years,artificial neural networks has good performance in many tasks of natural language processing,the application of neural network technology to text classification has also made many achievements.In the field of text classification based on deep learning,numerical representation of text and deep-learning-based text classification are two main research directions.The important technology of word embedding in text representation and the implementation principle and research status of deep learning method applied in text classification were systematically analyzed and summarized.And the shortcomings and the development trend of text classification methods in view of the current technology development were analyzed.…”
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Klasifikasi Kelas Kata (Part-Of-Speech Tagging) untuk Bahasa Madura Menggunakan Algoritme Viterbi by Ilham Firmansyah, Putra Pandu Adikara, Sigit Adinugroho

“…Banyak teknologi/aplikasi yang mengolah bahasa manusia, bidang tersebut bernama Natural Language Processing yang merupakan ilmu yang mempelajari untuk mengolah dan mengekstraksi bahasa manusia pada perkembangan teknologi. …”
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Enhancing Sentiment Analysis with a CNN-Stacked LSTM Hybrid Model by Shao Shuaijie

“…This paper focuses on developing a new hybrid model to solve sentiment analysis problems in Natural language processing. Sentiment analysis is a key branch of Natural language processing (NLP) and new models with better performance can boost the development of machine learning. …”
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The role of chromatin state in intron retention: A case study in leveraging large scale deep learning models. by Ahmed Daoud, Asa Ben-Hur

“…Complex deep learning models trained on very large datasets have become key enabling tools for current research in natural language processing and computer vision. By providing pre-trained models that can be fine-tuned for specific applications, they enable researchers to create accurate models with minimal effort and computational resources. …”
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Enhancing Persian text summarization through a three-phase fine-tuning and reinforcement learning approach with the mT5 transformer model by Vahid Nejad Mahmood Abadi, Fahimeh Ghasemian

“…In recent years, transformers have emerged as a prominent force in the landscape of natural language processing, particularly in the realm of text summarization. …”
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Sublemma-Based Neural Machine Translation by Thien Nguyen, Huu Nguyen, Phuoc Tran

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Design and Implementation of a Chatbot for Kurdish Language Speakers Using Chatfuel Platform by Hemn Karim Ahmed, Jamal Ali Hussein

“…Chatbots are mostly depend on Natural Language Processing (NLP). In this paper, the design and implementation of a chatbot are provided to help Kurdish speakers in using online conversations via texts to find answers instead of direct contact with human agents. …”
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POS Tagging Bahasa Madura dengan Menggunakan Algoritma Brill Tagger by Nindian Puspa Dewi, Ubaidi Ubaidi

“…Salah satunya adalah dengan melakukan penelitian tentang Bahasa Madura dalam bidang Natural Language Processing sehingga kedepannya pembelajaran tentang Bahasa Madura dapat dilakukan melalui media digital. …”
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Correlation between the Dissemination of Classic English Literary Works and Cultural Cognition in the New Media Era by Weiwei Guo

“…The use of natural language processing and knowledge graph technology can improve cultural cognition to promote the dissemination and development of classic English literature, which has become a necessary means of dissemination of classic English literature. …”
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6 Questions for Socially Aware Language Technologies by Diyi Yang

“… Over the last few decades, natural language processing (NLP) has dramatically improved performance and produced industrial applications like personal assistants. …”
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Research of phishing detection technology by Xi ZHANG, Zhi-wei YAN, Hong-tao LI, Guang-gang GENG

“…The current status of phishing scams were analyzed and the data sets and evaluation indicators commonly used in phishing detection were summaried.On this basis,a detailed overview of the typical methods of phishing detection was given,which included blacklist strategies,heuristic methods,visual matching methods,and methods based on machine learning and natural language processing.The comparison and analysis of those methods were given,and furtherly,the challenges and future trends of phishing detection were discussed.…”
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Frozen Weights as Prior for Parameter-Efficient Fine-Tuning by Xiaolong Ma, Peishun Liu, Haojie Gao, Zikang Yan, Ningning Ma, Wenqiang Liu, Xuefang Wang, Ruichun Tang

“…In the fields of natural language processing and computer vision, the emergence of large pre-trained models has led to the adoption of fine-tuning them for downstream tasks as an important paradigm. …”
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Large Language Models in Healthcare: A Bibliometric Analysis and Examination of Research Trends by Gencer G, Gencer K

“…The study highlights that neural network applications in diagnostic imaging, natural language processing for clinical documentation, and patient data in the field of general internal medicine, radiology, medical informatics, health care services, surgery, oncology, ophthalmology, neurology, orthopedics and psychiatry have seen significant growth in publications over the past two years. …”
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