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Artificial intelligence in chronic disease management

Below are some of the areas in which the technological advances in AI are ramping up the healthcare scenario.

Over the past two decades, chronic diseases have significantly increased among the population. The most prevalent conditions are cancer, heart diseases, and diabetes, among several others. Researchers are advancing the development of treatment options as these illnesses continue to proliferate. The medical industry is turning to the new technological advances in artificial intelligence (AI) to speed up the prevention, diagnosis, and treatment of several diseases. 

Today, artificial intelligence in chronic disease management is bringing radical changes in treating almost all sorts of bodily ailments. Below are some areas in which the technological advances in AI are ramping up the healthcare scenario. 

Heart Diseases 

At several medical institutions and organizations, researchers are taking steps to advance cardiovascular healthcare using AI. Hospitals and research centers are using AI-programmed computers to process data quickly and accurately to provide better treatment outcomes. AI programs can perform tasks including detecting and preventing heart disease, and improving diagnostic radiology capabilities. 

Read More: Paige To Deploy AI-Based Biomarker Test For Advanced Bladder Cancer

At Johns Hopkins University, researchers explored the use of whole-heart computational models to understand better ventricular arrhythmias, which can lead to personalized medical treatments for cardiovascular diseases. Researchers say that the patient-specific models can use predictive analytics to ascertain the outcomes of a cardiac procedure or the risk of sudden cardiac death.  

Recently, Apollo Hospitals, India partnered with Singapore-based organization ConnectedLife to avail an artificial intelligence tool to predict the risk of cardiovascular diseases and intervene early.

Cancer

Artificial intelligence has made early detection, prevention, and treatment relatively more straightforward for cancer. Researchers at Tulane University have discovered that AI can accurately diagnose colorectal cancer by analyzing tissue scans much better than pathologists. AI has consistently emerged as a boon for predicting or detecting cancers related to the bladder, breasts, and lungs. 

Artificial intelligence can also assist in determining the optimum course of treatment for patients. For patients with cancer, researchers are using predictive analytics to know how an individual will respond to a particular medication. AI and machine learning can also prevent unnecessary side effects from cancer treatments that may not work for some patients. 

Diabetes

Over the past several years, AI has been used by researchers to investigate methods for diabetes management. Different strategies for diabetic treatments include remote patient monitoring, self-management, and support from wearable AI devices.  

Individuals can track their blood sugar levels with continuous glucose monitors, which offer blood sugar estimates every five minutes. Models based on data analysis can predict the impact of meals and insulin on glucose levels, thus allowing patients to control blood sugar levels better. AI-backed mobile health tools have reduced the need for unnecessary patient-provider interaction and in-person appointments. Artificial intelligence also plays a vital role in diabetes prevention by identifying high-risk patients.  

Parkinson’s and Alzheimer’s disease

AI has also revolutionized the research, prevention, and treatment of Alzheimer’s and Parkinson’s diseases. Recently, the Michael J. Fox Foundation and the research arm of IBM developed an artificial intelligence model that can group typical symptom patterns of Parkinson’s disease. The AI model can accurately identify the progression of these symptoms in a patient, regardless of whether they are taking medications to mask those symptoms or not. 

A published research paper in Nature Portfolio explains how researchers have used machine learning techniques to look at the structural features inside the brain and identify Alzheimer’s disease at an early stage when it can be complicated to diagnose. The technology even scanned the regions not previously associated with Alzheimer’s. This new advancement can radically change the prevention and treatment options for Alzheimer’s patients. 

Conclusion

With the latest artificial intelligence technology, risk prediction models, and data analytics, practitioners can promptly identify warning signs of illnesses, allowing for a quick treatment turnaround and reduced healthcare costs. As researchers learn more about artificial intelligence capabilities, technology is becoming an effective tool for chronic disease prevention and management. With the rate at which new AI technologies are intervening in the medical industry today, healthcare is becoming more reliable and accessible for humankind. 

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Sahil Pawar
Sahil Pawar
I am a graduate with a bachelor's degree in statistics, mathematics, and physics. I have been working as a content writer for almost 3 years and have written for a plethora of domains. Besides, I have a vested interest in fashion and music.

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