Meta-Learner-Based Method for Classifying Skin Cancer Types from Dermoscopic Images Utilizing Deep Learning DOI
Abdulrahman Hassan Alhazmi

Lecture notes in computer science, Journal Year: 2024, Volume and Issue: unknown, P. 171 - 180

Published: Dec. 12, 2024

Language: Английский

Multi-residual attention network for skin lesion classification DOI
Haythem Ghazouani

Biomedical Signal Processing and Control, Journal Year: 2025, Volume and Issue: 103, P. 107449 - 107449

Published: Jan. 6, 2025

Language: Английский

Citations

0
Transformative Advances in AI for Precise Cancer Detection: A Comprehensive Review of Non-Invasive Techniques DOI
Hari Mohan, Joon Yoo, Serhii Dashkevych

et al.

Archives of Computational Methods in Engineering, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 11, 2025

Language: Английский

Citations

0
ECgMLP: A novel gated MLP model for enhanced endometrial cancer diagnosis DOI Creative Commons
Md. Alif Sheakh, Sami Azam,

Mst. Sazia Tahosin

et al.

Computer Methods and Programs in Biomedicine Update, Journal Year: 2025, Volume and Issue: unknown, P. 100181 - 100181

Published: Jan. 1, 2025

Citations

0
Cf-Wiad: Consistency Fusion with Weighted Instance and Adaptive Distribution for Enhanced Semi-Supervised Skin Lesion Classification DOI
Dandan Wang, Kang An,

Yaling Mo

et al.

Published: Jan. 1, 2025

Language: Английский

Citations

0
A Novel Transfer Learning Approach for Skin Cancer Classification on ISIC 2024 3D Total Body Photographs DOI
Javed Rashid, Salah Boulaaras, Muhammad Shoaib Saleem

et al.

International Journal of Imaging Systems and Technology, Journal Year: 2025, Volume and Issue: 35(2)

Published: March 1, 2025

ABSTRACT Skin cancer, and melanoma in particular, is a significant public health issue the modern era because of exponential death rate. Previous research has used 2D data to detect skin present methods, such as biopsies, are arduous. Therefore, we need new, more effective models tools tackle current problems quickly. The main objective work improve 3D ResNet50 model for cancer classification by transfer learning. Trained on ISIC 2024 Total Body Photographs (3D‐TBP), Kaggle competition dataset, aims five types cancer: Melanoma (Mel), Melanocytic nevus (Nev), Basal cell carcinoma (BCC), Actinic keratosis (AK), Benign (BK). While fine‐tuning achieves peak performance, augmentation addresses overfitting. proposed outperforms state‐of‐the‐art methods with an overall accuracy 93.88%. Since drops 85.67% while utilizing data, substantial contribution becomes apparent when working data. articulates excellent memory precision remarkable accuracy. According findings, improves diagnostic process may be rated better than conventional approaches noninvasive, accurate, efficient substitute. valuable it can help clinical application: early diagnosis melanoma.

Language: Английский

Citations

0
Skin Cancer Classifier: Performance Enhancement Using Deep Learning Models DOI
Swati Mishra, Megha Agarwal

2022 8th International Conference on Signal Processing and Communication (ICSC), Journal Year: 2025, Volume and Issue: unknown, P. 721 - 725

Published: Feb. 20, 2025

Language: Английский

Citations

0
Meta-Learner-Based Method for Classifying Skin Cancer Types from Dermoscopic Images Utilizing Deep Learning DOI
Abdulrahman Hassan Alhazmi

Lecture notes in computer science, Journal Year: 2024, Volume and Issue: unknown, P. 171 - 180

Published: Dec. 12, 2024

Language: Английский

Citations

0