Auto Response Generation in Online Medical Chat Services

  title={Auto Response Generation in Online Medical Chat Services},
  author={Hadi Jahanshahi and Syed Kazmi and Mucahit Cevik},
  journal={Journal of Healthcare Informatics Research},
  pages={344 - 374}
Telehealth helps to facilitate access to medical professionals by enabling remote medical services for the patients. These services have become gradually popular over the years with the advent of necessary technological infrastructure. The benefits of telehealth have been even more apparent since the beginning of the COVID-19 crisis, as people have become less inclined to visit doctors in person during the pandemic. In this paper, we focus on facilitating chat sessions between a doctor and a… 

Active Data Pattern Extraction Attacks on Generative Language Models

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CyBERT: Cybersecurity Claim Classification by Fine-Tuning the BERT Language Model

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Measuring the quality of patient-physician communication

The Text Classification of Theft Crime Based on TF-IDF and XGBoost Model

  • Zhang Qi
  • Computer Science
    2020 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA)
  • 2020
The results show that the XGBoost algorithm are better than KNN, Naïve Bayes, SVM and GBDT algorithm as classified theft crime data of a city from 2009 to 2019 based on text classification technology.

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There is an urgent need for a robust evaluation of diverse health care conversational agents’ formats, focusing on their acceptability, safety, and effectiveness.

Domain-Specific Language Model Pretraining for Biomedical Natural Language Processing

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SolutionChat: Real-time Moderator Support for Chat-based Structured Discussion

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