彭辰皓 Chen-Hao Peng

發明專利

國際研討會發表

1. H.-T. Hsiung, H.-W. Chang, C.-H. Peng, H. Woo, “Machine Learning-Based Prediction of Heavy Truck Tire and Brake Drum Temperatures from Vehicle Parameters”, 2025 East Asian Science, Technology and Society, Surakarta, Indonesia
2. C.-Y. Lee, C.-H. Peng, J.-Y. Chang, L.-C. Lai, T.-P. Lu, E.Y. Chuang, “Development of a deep learning-based approach for predicting microRNA targets and an integrated database”, The 6th Global Conference on Biomedical Engineering & Annual Meeting of TSBME 2024, Tainan, Taiwan
3. J.-Y. Chang, C.-H. Peng, L.-C. Lai, T.-P. Lu, E. Y. Chuang, C.-Y. Lee “MiRSystem2: An Advanced Online Tool for Predicting MicroRNA Targets and Their Biological Functions/Pathways”, 2024 International Conference on Intelligent Biology and Medicine, Houston, Texas, USA
4. J.-L. Fan‡, C.-H. Peng‡, D.-C. Cheng, Y.-C. Wang, “Cancer Survival Prediction Method Using Machine Learning and Deep Learning Models in Patients with Esophageal Squamous Cell Carcinoma,” The 37th IPPR Conference on Computer Vision, Graphics, and Image Processing, Hualien, Taiwan
5. J.-R. Wang‡, C.-H. Peng‡, Y.-J. Lee, N.-C. Tseng, D.-C. Cheng, “Unsupervised Automatic Staining Normalization and Intelligent Diagnosis of Lung Cancer Whole Slide Pathological Sections,” The 37th IPPR Conference on Computer Vision, Graphics, and Image Processing, Hualien, Taiwan
6. L.-H. Chen‡, C.-H. Peng‡, D.-C. Cheng, K.-J. Chen, “A Novel Multi-Classification Model for Colored Fundus Images Based on InceptionResNetV2 with Integrated Deep Features,” The 37th IPPR Conference on Computer Vision, Graphics, and Image Processing, Hualien, Taiwan
7. Y.-S. Pan‡, C.-H. Peng‡, C.-C. Hsiao, D.-C. Cheng, “Fully Automatic Breast Cancer Segmentation and Diagnosis: A Method Combining YOLOv8 and TinyVit,” The 37th IPPR Conference on Computer Vision, Graphics, and Image Processing, Hualien, Taiwan
8. K.-A. Hong‡, C.-H. Peng‡, N.-C. Tseng, D.-C. Cheng, “Enhancing Waste Classification Deep Learning Models Using Knowledge Distillation,” The 37th IPPR Conference on Computer Vision, Graphics, and Image Processing, Hualien, Taiwan
9. C.-H. Peng, H.-Y. Chen, D.-C. Cheng, E.Y. Chuang, C.-Y. Lee, “A CNN-based approach with efficient transfer learning improves microRNA-mRNA prediction,” American Association for Cancer Research Annual Meeting 2024, San Diego, California, USA
10. C.-H. Peng, W.-T. He, C.-L. Liu, T.-P. Lu, E.Y. Chuang, J.-M. Liou, C.-Y. Lee, “Predicting Atherosclerosis Risk Using Gut Microbiota Composition and Gramian Angular Difference Field Conversion”, Taiwan Society of Microbiology Annual Meeting 2023
11. C.-H. Peng, Jennifer Chen, H.-Y. Chen, E.Y. Chuang, C.-Y. Lee, “A groundbreaking prediction algorithm for microRNA-mRNA pairs employing a CNN-based deep learning model”, International Conference on Advanced Biomedical Sciences 2023
12. H.-K. Chang, H.-Y. Zeng, S.-R. Teng, Z.-J. Chang, C.-H. Peng*, “Diagnosis of SARS-CoV-2 Using Blood Parameters: An Alternative Screening Approach for Early Detection”, The 34th Annual International Society for Medical Innovation and Technology Conference 2023
13. C.-H. Peng, G. Zeng, J.-D. Leu, Y.-J. Lee, D.-C. Cheng, “Development of Computerized Reading and Scoring Program for Cofilin-1 Immunohistochemistry Stain”, The 16th Symposium of Medical Imaging and Radiological Sciences 2022
14. C.-H. Peng, H.-Y. Chen, W.-S. Li, P.-Y. Wang, J.-C. Li, D.-C. Cheng, “Enhancing Deep Learning Model Performance for Garbage Classification through Knowledge Distillation”, Conference on Information Technology and Application in Outlying Islands 2022
15. Y.-C. Yu.‡, C.-H. Peng‡, C.-Y. Lee, T.-C. Shih, D.-C. Cheng, T.-C. Wang, “AI-Precision Medicine Redefining Environmental Medicine: Predicting Noise-Induced Hearing Loss through Deep Learning-Based Feature Engineering”, Conference on Information Technology and Application in Outlying Islands 2022
16. C.-H. Peng, C.-C. Hsiao, F.-Z. Wu, D.-C. Cheng, “Malignant and Benign Lung Nodule Classification Based on Low Dose CT Images”, Annual Meeting of Taiwanese Society of Biomedical Engineering-Annual Report of Ministry of Science and Technology 2021
17. C.-H. Peng, D.-C. Cheng, Y.-J. Lee, “A Semi-Supervised Method to Classify Adenocarcinoma and Squamous Cell Carcinoma on Pathological Slides,” Annual Meeting of Taiwanese Society of Biomedical Engineering-Annual Report of Ministry of Science and Technology 2021

國際期刊論文

1. Z. Chang; G.-K. Xu; C.-H. Peng; K.-J. Chen; W. Liu, “Viscoelastic Mechanical Signature-Based Machine Learning for Assessment of Liver Fibrosis and Its Regression,” Int. J. Appl. Mech., 2024, [SCI, IF:2.9; Q2]
2. Z. Chang‡, C.-H. Peng‡, K.-J. Chen., G.-K. Xu., “Enhancing liver fibrosis diagnosis and treatment assessment: a novel biomechanical markers-based machine learning approach,” Phys. Med. Biol., 2024, [SCI, IF:3.5; Q2]
3. C.-C. Hsiao, C.-H. Peng, F.-Z. Wu, D.-C. Cheng, “Impact of Voxel Normalization on Machine Learning-Based Method: A Study on Pulmonary Nodule Malignancy Diagnosis Using LDCT,” Diagnostics, 2023, [SCI, IF:3.6; Q2]

國際期刊論文(同行審閱)

1. C.-H. Peng, J.-F. Wu, C.-J. Kuo, D.-C. Cheng, “Voxel Normalization in LDCT Imaging: Its Significance in Texture Feature Selection for Pulmonary Nodule Malignancy Classification: Insights from Two Centers”, Artificial Intelligence in Medicine, 2025, [SCI, IF:6.1; Q1]