Rajan Arora
Massive data sets and the development of artificial intelligence algorithms provide fresh perspectives and options for predicting cancer patients' unique mortality risks. The goal of the recently completed research was to construct an artificial intelligence survival prediction system for stomach cancer patients who were disease-free [1]. The artificial intelligence survival predicting system was created using the multi-task logistic regression algorithm, the cox survival regression method, and the random survival forest algorithm [2]. A transcription factor regulatory network of immune genes was created using 19 transcription factors and 70 immune genes [3]. Fourteen immunological genes were identified as prognostic indicators using multivariate Cox regression. Using these immune genes, a predictive signature for stomach cancer was created [4]. According to epidemiological data, gastric cancer is one of the most common digestive malignant tumours and the second highest cause of tumor-related fatalities, with fatalities in the prognosis for people with stomach cancer remained poor despite improvements in early screening, diagnosis, and therapies that somewhat lowered death [5]. Clinical factors that contribute to improve the prognosis of high risk GC patients include early detection of high mortality high risk GC patients and more accurate, customised therapy [6].
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