Automated Classification of Before-and-After Botox Faces Using Advanced Deep Learning Models
Abstract
Botox injections are a popular, non-invasive treatment in facial aesthetics, used to reduce wrinkles and achieve a youthful appearance. Accurate evaluation of Botox’s efficacy is essential in clinical settings, yet it is often subject to subjective interpretation. This study presents an automated, objective approach for classifying pre- and post-Botox facial images using advanced deep-learning models, including MobileNet, ResNet50, and InceptionV3. The models were trained on a diverse dataset of facial images, achieving high performance in classifying treatment outcomes. InceptionV3 demonstrated the highest accuracy (89.27%), precision (91.15%), and recall (92.27%), with statistically significant differences across models (p < 0.05) for all metrics. While InceptionV3 and ResNet50 excelled in accuracy and recall, MobileNet offered a computationally efficient option suited for real-time applications.
References
Bouguila J, Khochtali H. Facial plastic surgery and face recognition algorithms: interaction and challenges. A scoping review and future directions. Journal of stomatology, oral and maxillofacial surgery. 2020 Dec 1;121(6):696-703. doi: https://doi.org/10.1016/j.jormas.2020.06.007
Park MY, Ahn KY. Scientific review of the aesthetic uses of botulinum toxin type A. Archives of craniofacial surgery. 2021 Feb;22(1):1. https://doi.org/10.7181/acfs.2021.00003
M. Smith A, Ferris T, K. Nahar V, Sharma M. Non-traditional and non-invasive approaches in facial rejuvenation: a brief review. Cosmetics. 2020 Feb 12;7(1):10. doi: https://doi.org/10.3390/cosmetics7010010
Niamtu J. Cosmetic Facial Surgery-E-Book. Elsevier Health Sciences; 2022 Mar 22. https://shop.elsevier.com/books/cosmetic-facial-surgery/niamtu/978-0-323-79519-7
Sethi N, Singh S, DeBoulle K, Rahman E. A review of complications due to the use of botulinum toxin A for cosmetic indications. Aesthetic plastic surgery. 2021 Jun;45:1210-20. doi: https://doi.org/10.1007/s00266-020-01983-w
https://www.kaggle.com/datasets/trainingdatapro/botox-injections-before-and-after/data
Mahmoudiandehkordi S, Yeganegi M, Shomalzadeh M, Ghasemi Y, Kalatehjari M. Enhancing IVF Success: Deep Learning for Accurate Day 3 and Day 5 Embryo Detection from Microscopic Images. International Journal of Applied Data Science in Engineering and Health. 2024 Aug 14;1(1):18-25. https://ijadseh.com/index.php/ijadseh/article/view/5
Abbasi H, Afrazeh F, Ghasemi Y, Ghasemi F. A Shallow Review of Artificial Intelligence Applications in Brain Disease: Stroke, Alzheimer's, and Aneurysm. International Journal of Applied Data Science in Engineering and Health. 2024 Oct 5;1(2):32-43. https://ijadseh.com/index.php/ijadseh/article/view/12
Afrazeh F, Shomalzadeh M. Revolutionizing Arthritis Care with Artificial Intelligence: A Comprehensive Review of Diagnostic, Prognostic, and Treatment Innovations. International Journal of Applied Data Science in Engineering and Health. 2024 Sep 10;1(2):7-17. https://ijadseh.com/index.php/ijadseh/article/view/8
Chen H, Kim S, Hardie JM, Thirumalaraju P, Gharpure S, Rostamian S, Udayakumar S, Lei Q, Cho G, Kanakasabapathy MK, Shafiee H. Deep learning-assisted sensitive detection of fentanyl using a bubbling-microchip. Lab on a Chip. 2022;22(23):4531-40. https://doi.org/10.1039/d2lc00478j
Dodda S, Chintala S, Kanungo S, Adedoja T, Sharma S. Exploring AI-driven Innovations in Image Communication Systems for Enhanced Medical Imaging Applications. Journal of Electrical Systems. 2024;20(3s):949-59. doi: https://journal.esrgroups.org/jes/article/view/1409
Nafissi N, Heiranizadeh N, Shirinzadeh-Dastgiri A, Vakili-Ojarood M, Naseri A, Danaei M, Saberi A, Aghasipour M, Shiri A, Yeganegi M, Rahmani A. The Application of Artificial Intelligence in Breast Cancer. EJMO. 2024;8(3):235-44. doi: https://doi.org/10.14744/ejmo.2024.45903
Zi Y, Wang Q, Gao Z, Cheng X, Mei T. Research on the application of deep learning in medical image segmentation and 3d reconstruction. Academic Journal of Science and Technology. 2024 Apr 15;10(2):8-12. doi: https://drpress.org/ojs/index.php/ajst/article/view/20172
Orouskhani M, Zhu C, Rostamian S, Zadeh FS, Shafiei M, Orouskhani Y. Alzheimer's disease detection from structural MRI using conditional deep triplet network. Neuroscience Informatics. 2022 Dec 1;2(4):100066. doi: http://dx.doi.org/10.1016/j.neuri.2022.100066
Shiwlani A, Ahmad A, Umar M, Dharejo N, Tahir A, Shiwlani S. BI-RADS Category Prediction from Mammography Images and Mammography Radiology Reports Using Deep Learning: A Systematic Review. Jurnal Ilmiah Computer Science. 2024 Jul 15;3(1):30-49. https://ejurnal.snn-media.com/index.php/jics/article/view/31
Kharaji M, Abbasi H, Orouskhani Y, Shomalzadeh M, Kazemi F, Orouskhani M. Brain Tumor Segmentation with Advanced nnU-Net: Pediatrics and Adults Tumors. Neuroscience Informatics. 2024 Feb 22:100156. doi: https://dx.doi.org/10.2139/ssrn.4514619
Altmann S, Grauhan NF, Brockstedt L, Kondova M, Schmidtmann I, Paul R, Clifford B, Feiweier T, Hosseini Z, Uphaus T, Groppa S. Ultrafast brain MRI with deep learning reconstruction for suspected acute ischemic stroke. Radiology. 2024 Feb 20;310(2):e231938. doi: https://doi.org/10.1148/radiol.231938
Minoo S, Ghasemi F. Automated Teeth Disease Classification using Deep Learning Models. International Journal of Applied Data Science in Engineering and Health. 2024 Sep 18;1(2):23-31. https://ijadseh.com/index.php/ijadseh/article/view/10
Duong TV, Vy VP, Hung TN. Artificial intelligence in plastic surgery: advancements, applications, and future. Cosmetics. 2024 Jun 27;11(4):109. doi: https://doi.org/10.3390/cosmetics11040109
Brenac, C., Fazilat, A.Z., Fallah, M., Kawamoto-Duran, D., Sunwoo, P.S., Longaker, M.T., Wan, D.C. and Guo, J.L., 2024. AI in plastic surgery: customizing care for each patient. Artificial Intelligence Surgery, 4(4), pp.296-315. doi: https://doi.org/10.20517/ais.2024.49
Barone M, De Bernardis R, Persichetti P. Artificial intelligence in plastic surgery: Analysis of applications, perspectives, and psychological impact. Aesthetic Plastic Surgery. 2024 Mar 12:1-3. doi: https://doi.org/10.1007/s00266-024-03988-1
Atkinson CJ, Seth I, Xie Y, Ross RJ, Hunter-Smith DJ, Rozen WM, Cuomo R. Artificial intelligence language model performance for rapid intraoperative queries in plastic surgery: ChatGPT and the deep Inferior epigastric perforator flap. Journal of Clinical Medicine. 2024 Feb 4;13(3):900. doi: https://doi.org/10.3390/jcm13030900
Teven CM, Howard MA. Artificial intelligence in plastic surgery. In Artificial Intelligence in Clinical Practice 2024 Jan 1 (pp. 245-249). Academic Press.
Park YY, Kim KK, Park B. A Comprehensive Assessment of Soft-tissue Sagging after Zygoma Reduction Surgery through Artificial Intelligence Analysis. Plastic and Reconstructive Surgery–Global Open. 2024 Aug 1;12(8):e6055. doi: https://doi.org/10.1097/gox.0000000000006055
Aktar Ugurlu G, Ugurlu BN, Yalcinkaya M. Evaluating the Impact of BoNT-A Injections on Facial Expressions: A Deep Learning Analysis. Aesthetic Surgery Journal. 2024 Oct 4:sjae204. doi: https://doi.org/10.1093/asj/sjae204
Souza S, Bhethanabotla RM, Mohan S. Applications of artificial intelligence in facial plastic and reconstructive surgery: a systematic review. Current Opinion in Otolaryngology & Head and Neck Surgery. 2024 Apr 22:10-97. doi: https://doi.org/10.1097/moo.0000000000000975
Ge XX, Wang WF, Patnaik LM. A Novel Deep Neural Network for Facial Beauty Improvement. Journal of Computers. 2024 Feb;35(1):97-107. doi: https://doi.org/10.53106/199115992024023501007
Khan A, Galarraga O, Garcia-Salicetti S, Vigneron V. Phase-Based Gait Prediction after Botulinum Toxin Treatment Using Deep Learning. Sensors. 2024 Aug 18;24(16):5343. doi: https://doi.org/10.3390/s24165343