@inproceedings{10043998,author={Ghadiri, Ali and Sheikholeslami, Afrooz and Bahaloo, Asiyeh},booktitle={2022 8th Iranian Conference on Signal Processing and Intelligent Systems (ICSPIS)},title={Multi-label detection of ophthalmic disorders using InceptionResNetV2 on multiple datasets},year={2022},volume={},number={},pages={1-6},doi={10.1109/ICSPIS56952.2022.10043998}}
INFUS 2021
A Fuzzy Deep Learning Approach to Health-Related Text Classification
Nasser Ghadiri, Ali Ghadiri, and Afrooz Sheikholeslami
In Intelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation, 2022
Following the tremendous amounts of text generated in social networks and news channels, and gaining valuable and dependable insights from diverse sources of information is a tedious task. The challenge is increased during specific periods, for example, in a pandemic event like Covid-19. Existing text categorization methods, such as sentiment classification, aim to help people tackle this challenge by categorizing and summarizing the text content. However, the inherent uncertainty of user-generated text limits their efficiency. This paper proposes a novel architecture based on fuzzy inference and deep learning for sentiment classification that overcomes this limitation. We evaluate the proposed method by applying it to well-known health-related text datasets and comparing the accuracy with state-of-the-art methods. The results show that the proposed fuzzy fusion methods increase the accuracy compared to individual pretrained models. The model also provides an expressive architecture for health news classification.
@inproceedings{10.1007/978-3-030-85577-2_21,author={Ghadiri, Nasser and Ghadiri, Ali and Sheikholeslami, Afrooz},editor={Kahraman, Cengiz and Cebi, Selcuk and Cevik Onar, Sezi and Oztaysi, Basar and Tolga, A. Cagri and Sari, Irem Ucal},title={A Fuzzy Deep Learning Approach to Health-Related Text Classification},booktitle={Intelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation},year={2022},publisher={Springer International Publishing},address={Cham},pages={179--186},isbn={978-3-030-85577-2}}