Cardiovascular disease continues to be a major concern, and the electrocardiogram (ECG) is a proven non-invasive technique for detecting cardiac issues. Traditional diagnosis, on the other hand, is based on an individual patient’s medical history and clinical examinations, which are ineffective owing to diverse data. By analyzing the electrical activity of the heart, AI is being used to identify prognostic arrhythmias such as atrial fibrillation. Deep convolutional neural networks (CNNs) are the basic building blocks of machine learning algorithms used in cardiovascular medicine to analyze ECG data. The adoption and use of AI-based diagnostic tools in clinical settings, however, may be limited by issues with interpretability and openness, such as evaluating models’ performance across datasets, processing power consumption, privacy and security concerns, imbalanced and limited datasets, and lack of clear guidelines for CNNs. Nevertheless, these technologies offer standardization, continuous, real-time monitoring, and more accurate interpretation—all of which have the potential to improve patient outcomes. This blog provides an overview of AI technologies applied and the challenges associated with the ECG in the diagnosis of cardiovascular diseases.
Breast cancer is a diverse disease with varying clinical presentations, morphologic features, and molecular characteristics. It is influenced by various genetic pathways and is a major trend in breast cancer care. Neoadjuvant chemotherapy is a major trend, requiring integrated multidisciplinary care from pathologists, radiologists, surgeons, and oncologists. Anti-HER2 therapy has improved clinical results for HER2-positive breast cancer patients.
Pertuzumab, a humanized monoclonal antibody, targets the extracellular dimerization domain of HER2, inhibiting downstream signaling and cell survival pathways. It is used in conjunction with trastuzumab and docetaxel to treat HER2-positive metastatic breast cancer. In addition to directly encouraging the death of cancer cells, monoclonal antibodies also trigger immunological activation, which is deadly to tumour cells.
Pertuzumab possesses the capability to elicit immune effector responses, including cell-mediated cytotoxicity that is dependent on antibodies. The antibody targets the PI3K/AKT and RAS/MEK/ERK pathways, protecting normal cells from suicide. It can activate immunological effector mechanisms, such as antibody-dependent cell-mediated cytotoxicity. Trastuzumab and pertuzumab function in complementary ways, highlighting the importance of understanding the biology of this devastating disease. This blog focuses on the mechanism of pertuzumab in patients with early-stage HER2-positive breast cancer receiving neoadjuvant treatment.