Abstract Background/Introduction Artificial intelligence (AI) in the healthcare sector is
receiving attention from researchers and health professionals. Few previous studies have …

Cervical cancer remains a leading cause of cancer death in women, seriously threatening
their physical and mental health. It is an easily preventable cancer with early screening and …

Traditional screening of cervical cancer type classification majorly depends on the
pathologist's experience, which also has less accuracy. Colposcopy is a critical component …

The increasing use of machine learning (ML) algorithms in clinical settings raises concerns
about bias in ML models. Bias can arise at any step of ML creation, including data handling …

Accurate early detection of breast and cervical cancer is vital for treatment success. Here, we
conduct a meta-analysis to assess the diagnostic performance of deep learning (DL) …

Objective: The likelihood of timely treatment for cervical cancer increases with timely
detection of abnormal cervical cells. Automated methods of detecting abnormal cervical cells …

Discrimination of ovarian tumors is necessary for proper treatment. In this study, we
developed a convolutional neural network model with a convolutional autoencoder (CNN …

Background Colposcopy is indispensable for the diagnosis of cervical lesions. However, its
diagnosis accuracy for high‐grade squamous intraepithelial lesion (HSIL) is at about 50 …

Digital clinical histopathology technique is used for accurately diagnosing cancer cells and
achieving optimal results using Internet of Things (IoT) and blockchain technology. The cell …

Background. Biobanks are vital research infrastructures aiming to collect, process, store, and
distribute biological specimens along with associated data in an organized and governed …