How Health Technology Tools Help Manage Cardiometabolic Disease

India is prone to cardiovascular illnesses. As the leading cause of mortality worldwide, cardiovascular disease (CVD) is projected to have killed 17,8 million individuals in India, accounting for 32 percent of the global disease burden. Cardiometabolic illnesses are a subset of CVDs that frequently develop in tandem, have a shared aetiology, and exacerbate one another when they coexist. It is related with nonalcoholic fatty liver disease, myocardial infarction, stroke, diabetes, obesity, insulin resistance, and hypertension.

Currently, the incidence of cardiometabolic disorders is rising, and it is expected that a person will encounter at least one of them in his lifetime. Nonetheless, it is essential to recognise that many cardiometabolic disorders are fully avoidable and result from unhealthy lifestyles, behavioural patterns, and behaviours. They are detrimental to health and fitness. They do not exist in isolation, but come in unique combinations, complexity, and levels of sharpness for each individual. If left untreated, they can have grave and even deadly consequences.

A scientific theory asserts that cardiometabolic illnesses are progressive, chronic conditions with limited remission potential. Although the deployment of AI-powered technology in healthcare has made Diabetes Mellitus remission feasible, this treatment strategy is still viewed with suspicion by medical professionals and patients.

Despite the research and innovative medicines committed to them, diabetes and hypertension are anticipated to become significant health care concerns in the future years. In the near future, its incidence is anticipated to multiply exponentially. Consequently, the status quo has failed. Traditional therapies tend to treat only the symptoms, not the underlying cause. The scientific community must transition from illness management to a new standard of care that focuses on reversing the disease process and fostering recovery. Exists a ready-made strategy for controlling this behemoth of metabolic diseases?

A patient with one of these metabolic illnesses not only has a significant risk of morbidity and death, but also a substantial cost burden due to the need for lifetime therapy. These lifestyle-related disorders impose monetary costs on individuals, communities, organisations, and employers. According to the existing laws governing insurance coverage for all employees, those with chronic metabolic illnesses are the most costly.

Type 2 diabetes is among the most costly conditions to insure. According to studies, 80% of cardiometabolic disorder-related fatalities occur in low- and middle-income nations. This is worrisome and distressing, given that many of these poor nations would have to spend billions of rupees on diseases that were genuinely avoidable, and that lifestyle change is their primary method of therapeutic management.

Now the question is whether artificial intelligence is the solution.

In recent years, with the growth and improvement of AI technology, it has increasingly gone from theory to practise. The numerous medical uses of AI are illustrated. In addition, AI technology has evolved into a crucial component that may drive the growth of the medical business and enhance the quality of medical services. AI can assist physicians with illness diagnosis and therapy optimization.

AI, when applied to conventional medical processes, can reduce the rate of incorrect diagnoses and increase diagnostic efficiency. AI can also detect medical pictures and deliver more accurate diagnostic imaging data to physicians. Using big data analytics, AI systems can frequently deliver more precise patient prognoses and illness forecasts.

The most recent advancement in health monitoring technology enables the creation of dynamic digital copies of any patient’s metabolism based on hundreds of digital data points acquired from non-invasive sensors and self-reported patient preferences. Personalised, precise, and individualised information regarding diet, sleep, exercise, and breathing processes is created with the use of AI.

In addition to creating an accurate digital reproduction of an individual’s metabolism, it is also feasible to forecast future events caused by the illness process. This will aid in implementing remedial measures to avert the looming disaster.

Using AI-powered technology in the illness management process can theoretically result in weight reduction, remission of diabetes, and reversal of harmful metabolic state. AI is on the rise and will play a crucial role in the therapy of chronic cardiometabolic conditions. Perhaps, in the near future, these illnesses will be as treatable as infections.

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