A new study has shown that artificial intelligence can be a powerful tool to predict early deaths in chronic inflammatory bowel patients, especially if your chronic health conditions are diagnosed in the early life stages. The study published in the Journal of the Canadian Medical Association revealed that about half of the deaths due to the diseases of chronic inflammation “they die prematurely”. The study, which used the machine learning models to predict deaths, sheds light on the health risks facing chronic inflammatory patients, especially as they develop other chronic health conditions in the early stages of their lives. The researchers have succeeded in analyzing healthy data to identify patients with a greater risk of death before the age of 75, as models show a high accuracy of prediction, which can help help preventative and treatment efforts to help more needy patients, which can provide more coordinated and effective health care. Digestive disorders said the researchers said that artificial intelligence could play an important role in improving health results for patients with chronic intestinal inflammation, and reduced the number of early deaths associated with this condition. Chronic intestinal inflammation is a set of chronic inflammatory disorders that mainly affect the digestive system, including “Crohn” disease and ulcerative colitis. Canada is one of the countries that has the highest rate of chronic intestinal inflammation in the world, where there are expected to live about 470,000 people (equivalent to 1 in 91 people) with this condition with 2035. Chronic intestinal inflammatory patients have a higher mortality rate (17 compared to 12 per 1,000 people annually) compared to non -injured, with a larger middle of the middle of the middle and average of 59 years) for women and 6 years for men. Early deaths (known before the age of 75) are a strong indication of the health of the population and the performance of the health system, as many of these deaths can be avoided by appropriate prevention or early and effective treatment. Understanding factors that predict early deaths can help improve health systems, and to target preventative efforts to most risk groups. An increased risk of death The multiple of chronic illnesses indicate that there are two or more cases of chronic health cases in the same person, and patients with chronic intestinal inflammation have a greater likelihood of developing other chronic health conditions compared to non -injured. The multiple of chronic diseases can change the natural path of chronic intestinal inflammation, exacerbating the symptoms and increasing the risk of death. Generally, the multitude of chronic diseases is associated with complex care plans, ill health results and an increase in the number of deaths. During the study, the machine learning models were used to predict early death in the general population, showing the ability to determine data patterns that can guide causal research. Artificial intelligence techniques have also been applied to analyze healthy data for chronic intestinal inflammatory patients in Ontario, Canada, with the aim of predicting early deaths, and administrative health data has been used from the IES institute, which has an extensive database for more than 99% of the province. The study included an analysis of 9278 databesteries for patients with chronic inflammation between 2010 and 2020. Chronic health conditions have been identified using approved algorithms, including asthma, heart failure, chronic obstructive pulmonary disease, diabetes, rheumatoid arthritis, high blood pressure and dementia. The cancer was also identified by the cancer record in Ontario, where data was divided into training and test groups (by 80:20) and the use of three predictive tasks, the first focused on chronic health conditions during death, while the second on cases diagnosed before the age of 60 focused, while the third rely on the normal age. Treatment development has been developed and machine learning models have been developed using advanced techniques to determine the best model that can predict early death. The results showed that these models could identify patients with a greater risk of premature death, giving the opportunity to improve healthcare and direct preventive efforts to the most vulnerable groups. The results also showed that about 47% of the deaths of chronic intestinal inflammatory patients were early, with the increase in men compared to women (50% compared to 44%). The most common chronic health conditions included arthritis (77%), high blood pressure (73%), mood disorders (69%), kidney failure (50%) and cancer (46%). The researchers emphasized that the use of early death as a study of study helps to determine the chances of improving the health system, as many of these deaths can be avoided by appropriate prevention or early and effective treatment. They pointed out that results provide scientific support for providing multidisciplinary and integrated healthcare throughout the life of patients, especially during the youth and middle life stage. The study hopes to help identify areas that need to be more monitored by a group of health professionals, including nutritionists, mental health and specialized doctors. The researchers also hope that their results will contribute to the development of more effective preventative and therapeutic strategies for patients with chronic intestinal inflammation.
Study: Artificial Intelligence can predict early deaths for patients with chronic intestinal inflammation
