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2. Automated entry of paper-based patient-reported outcomes: Applying deep learning to the Japanese orthopaedic association back pain evaluation questionnaire.

Author

Kita K, Fujimori T, Suzuki Y, Kaito T, Takenaka S, Kanie Y, Furuya M, Wataya T, Nishigaki D, Sato J, Tomiyama N, Okada S, and Kido S

Subjects
Humans, Quality of Life, Japan, Back Pain, Surveys and Questionnaires, Low Back Pain diagnosis, Low Back Pain therapy, Orthopedics, Deep Learning
Abstract

Background: Health-related patient-reported outcomes (HR-PROs) are crucial for assessing the quality of life among individuals experiencing low back pain. However, manual data entry from paper forms, while convenient for patients, imposes a considerable tallying burden on collectors. In this study, we developed a deep learning (DL) model capable of automatically reading these paper forms., Methods: We employed the Japanese Orthopaedic Association Back Pain Evaluation Questionnaire, a globally recognized assessment tool for low back pain. The questionnaire comprised 25 low back pain-related multiple-choice questions and three pain-related visual analog scales (VASs). We collected 1305 forms from an academic medical center as the training set, and 483 forms from a community medical center as the test set. The performance of our DL model for multiple-choice questions was evaluated using accuracy as a categorical classification task. The performance for VASs was evaluated using the correlation coefficient and absolute error as regression tasks., Result: In external validation, the mean accuracy of the categorical questions was 0.997. When outputs for categorical questions with low probability (threshold: 0.9996) were excluded, the accuracy reached 1.000 for the remaining 65 % of questions. Regarding the VASs, the average of the correlation coefficients was 0.989, with the mean absolute error being 0.25., Conclusion: Our DL model demonstrated remarkable accuracy and correlation coefficients when automatic reading paper-based HR-PROs during external validation., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Published
2024
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6. Parametric Comparison of Deep Learning Models for Musculoskeletal Abnormality Detection

Author

Raghunath, Niharika Gowri, Harikumar, Nandana, Sree, Paladi Navya, Sougandheeka, Kothuru Eesha, Vanamala, H. R., Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Nagar, Atulya K., editor, Jat, Dharm Singh, editor, Mishra, Durgesh Kumar, editor, and Joshi, Amit, editor

Published
2024
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7. A Review of Relationship Extraction Based on Deep Learning

Author

Liao, Guolong, Tang, Xiangyan, Li, Tian, Zhong, Li, Zeng, Pengfan, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Jin, Hai, editor, Pan, Yi, editor, and Lu, Jianfeng, editor

Published
2024
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8. Deep Learning Based SQL Injection Attack Detection

Author

Pan, Zhang, Huang, Qianli, Tian, Ziqing, Liu, Ying, Lou, Jiapeng, Gong, Yongguang, Wang, Zhiqiang, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Jin, Hai, editor, Pan, Yi, editor, and Lu, Jianfeng, editor

Published
2024
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10. Vision-Based Human Activity Recognition Using CNN and LSTM Architecture

Author

Gupta, Neha, Malik, Payal, Dubey, Arun Kumar, Jain, Achin, Yadav, Sarita, Verma, Devansh, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Garg, Deepak, editor, Rodrigues, Joel J. P. C., editor, Gupta, Suneet Kumar, editor, Cheng, Xiaochun, editor, Sarao, Pushpender, editor, and Patel, Govind Singh, editor

Published
2024
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