Insights into AI advances in immunohistochemistry for effective breast cancer treatment: a literature review of ER, PR, and HER2 scoring.

Breast cancer is a significant health challenge, with accurate and timely diagnosis being critical to effective treatment. Immunohistochemistry (IHC) staining is a widely used technique for the evaluation of breast cancer markers, but manual scoring is time-consuming and can be subject to variability. With the rise of Artificial Intelligence (AI), there is an increasing interest in using machine learning and deep learning approaches to automate the scoring of ER, PR, and HER2 biomarkers in IHC-stained images for effective treatment.

Stain color translation of multi-domain OSCC histopathology images using attention gated cGAN.

Oral Squamous Cell Carcinoma (OSCC) is the most prevalent type of oral cancer across the globe. Histopathology examination is the gold standard for OSCC examination, where stained histopathology slides help in studying and analyzing the cell structures under a microscope to determine the stages and grading of OSCC. One of the staining methods popularly known as H&E staining is used to produce differential coloration, highlight key tissue features, and improve contrast, which makes cell analysis easier.

Isoform-Specific Role of Akt in Oral Squamous Cell Carcinoma.

Protein kinase B (Akt) plays a very significant role in various cancers including oral cancer. However, it has three isoforms (Akt1, Akt2, and Akt3) and they perform distinct functions and even play contrasting roles in different cancers. Therefore, it becomes essential to evaluate the isoform-specific role of Akt in oral cancer.