This study evaluates the quality of published research using artificial intelligence (AI) for
ovarian cancer diagnosis or prognosis using histopathology data. A systematic search of …

The diagnosis of cancer is typically based on histopathological sections or biopsies on glass
slides. Artificial intelligence (AI) approaches have greatly enhanced our ability to extract …

PURPOSE Cancers with homologous recombination deficiency (HRD) can benefit from
platinum salts and poly (ADP-ribose) polymerase inhibitors. Standard diagnostic tests for …

BRCA1 and BRCA2 genes play a crucial role in repairing DNA double-strand breaks
through homologous recombination. Their mutations represent a significant proportion of …

Estrogen receptor (ER) positivity by immunohistochemistry has long been a main selection
criterium for breast cancer patients to be treated with endocrine therapy. However, ER …

Simple Summary In canine urothelial carcinoma, the BRAF gene is frequently mutated
(V595E). To detect this mutation, urine or tissue samples are currently tested by PCR …

The utilization of PARP inhibitors (PARPis) has significantly improved the prognosis for
ovarian cancer patients. However, as the use of PARPis increases, the issue of PARPi …

High-grade serous ovarian cancer (HGSC) is the most common subtype of ovarian cancer.
HGSC patients typically present with advanced disease, which is often resistant to …

The initial enthusiasm about computational pathology (CP) and artificial intelligence (AI) was
that they will replace pathologists entirely on the way to fully automated diagnostics. It is …

Background The status of BRCA1/2 genes plays a crucial role in the treatment decision-
making process for multiple cancer types. However, due to high costs and limited resources …