A Review on Diagnosing Gastric Cancer using a Tri-Algorithm Gastronet

Gastric cancer (GC) is a widespread malignant tumour that unfortunately carries a bleak prognosis. Detecting it early is crucial, and for this, endoscopic examination plays a vital role. However, further treatment necessitates pathological confirmation and CT scanning. Despite medical advancements, gastric cancer remains a deadly disease, challenging our efforts to improve prognosis. In pursuit of more accurate gastric cancer diagnosis, a project has been undertaken to develop a method using deep learning algorithms. This approach recognizes the substantial number of tests involved in reaching a conclusive diagnosis. The proposed deep learning algorithm, known as Gastronet, has shown promising results. Gastronet is a unique combination of three different algorithms: Multi-task Net, Fusion Net, and Global Net. Through their collaboration, Gastronet offers precise predictions of gastric cancer without the need for additional diagnostic procedures. The implementation of this advanced algorithm contributes significantly to the effective and accurate diagnosis of gastric cancer, surpassing the capabilities of existing models