A Novel Web Framework for Cervical Cancer Detection System: A Machine Learning Breakthrough

• Published in: IEEE access Vol. 12; pp. 41542 - 41556
• Main Authors: Qathrady, Mimonah Al, Shaf, Ahmad, Ali, Tariq, Farooq, Umar, Rehman, Aqib, Alqhtani, Samar M., Alshehri, Mohammed S., Almakdi, Sultan, Irfan, Muhammad, Rahman, Saifur, Bade Eljak, Ladon Ahmed
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Accuracy; Algorithms; Artificial neural networks; Biophysics; Biopsy; Cancer; Cervical cancer; cervical cancer detection; Decision analysis; Decision trees; Detection algorithms; Diagnosis; Expert web framework; gyne cancer diagnosis; Health care; Human papillomavirus; Internet of Things; Machine learning; Medical diagnosis; Support vector machines; Web servers; Web sites

Cervical cancer, the second most prevalent cancer among women worldwide, is primarily attributed to the human papillomavirus (HPV). Despite advances in healthcare, it remains a significant cause of mortality among women across diverse regions, surpassing other hereditary cancers. Early detection is...