Cardiovascular diseases are a significant problem worldwide, with millions dying annually due to these ailments. While technology has improved detection, researchers are taking the next step by employing artificial intelligence (AI) to help patients with coronary heart disease, cerebrovascular disease and other conditions. Can AI detect cardiovascular disease? Here’s how AI will affect the future of cardiovascular healthcare. Can AI Detect Cardiovascular Disease? The medical field has rapidly adopted AI to improve healthcare outcomes, with hospitals finding ways to integrate it into daily operations. Here are four recent innovations helping researchers equip this advanced technology and identify heart disease. Analyzing Genes In early 2023, researchers from Rutgers University discussing genetic analysis and how AI and machine learning (ML) can identify cardiovascular disease. The Rutgers Institute for Health used AI to examine healthy people and those with heart disease and was able to link genes to cardiovascular issues. published a study Researchers found correlations with age and gender and concluded the risk of cardiovascular disease increases with age. The Rutgers study trained its model to detect patients at high risk for heart issues. It was able to predict the association with heart failure, atrial fibrillation, and other risks based on demographics. Studying Cells Putting cells under the microscope is another effective way to identify cardiovascular disease using AI. Researchers at the University of East London have wielded AI to and determine who is more at risk. The scientists isolated miniature stem cell hearts and placed them in a petri dish. As they age, the trained model can predict which sets are more at risk and will become faulty. study cells with heart disease While tiny, the stem cells function like a living human heart with a consistent heartbeat. They have heart disease, allowing the East London researchers to train its AI as a diagnostic tool. With this information, the university’s researchers are using AI to understand its connection with aging and improve treatment for those with the disease. Prashant Ruchaya, a senior lecturer at the University of East London, has spearheaded the research and says the technology is crucial for the future of heart disease mitigation. “Cardiovascular disease remains the leading cause of mortality worldwide, and aging is a significant risk factor for its development,” Ruchaya said. “Our research aims to comprehensively explore how aging influences the mechanisms underlying heart diseases, ultimately leading to innovative approaches in mitigating the impact of cardiovascular conditions on older populations. “We are working on cutting-edge research here in developing new disease models and developing AI to predict disease earlier and to develop new treatments to treat heart disease.” Examining MRIs Another AI innovation in the United Kingdom comes from St. Bartholomew’s Hospital in London, where experts have advanced technology to find heart disease more rapidly. The researchers say they can using AI during its pilot, leading to more hospitals using the technology. The National Health Service (NHS) says it will spread the AI-assisted detector to various facilities across its system. detect heart disease in 20 seconds In this instance, the AI examines the MRI in real time, shortening the time necessary for analysis. The NHS says cardiologists need at least 13 minutes to check the MRI scans, so reducing the wait to 20 seconds would drastically reduce this gap and help healthcare providers. Other benefits of this AI system include waiting about 33% less time for results and reducing misclassifications, thus improving treatments. Inspecting Heart Dimensions Healthcare experts also use AI to detect cardiovascular diseases based on the heart’s dimensions. Researchers at Cedars-Sinai Medical Center for detecting diseases — hypertrophic cardiomyopathy and cardiac amyloidosis — you might overlook when examining the heart. Can AI detect a cardiovascular disease that’s difficult to find? have developed an AI tool The researchers trained the AI based on 34,000 ultrasound videos to distinguish various sections of the heart. Identifying the thickness of a heart’s walls and the size of its chambers helps the AI know when abnormalities occur. With this information, healthcare providers will better understand which patients are more at risk for cardiovascular diseases — especially underdiagnosed conditions like hypertrophic cardiomyopathy and cardiac amyloidosis. Implications of Using AI Detection for Heart Disease Cardiologists have opportunities for improved diagnoses and treatments as AI usage increases in healthcare. Here are some of the implications of using AI for detecting cardiovascular diseases. Early Treatment As Ruchaya said, heart disease is the leading cause of death, with the World Health Organization estimating worldwide. Heart attacks and strokes are responsible for more than 80% of deaths, and about one-third occur in people under 70 years old. Early detection of heart disease is crucial, and healthcare providers can achieve diagnoses quicker with AI. nearly 18 million annual deaths AI tools use algorithms with vast amounts of data stored inside their systems. When directed, the AI can reference this historical information to examine a patient’s heart and determine their disease risk. While cardiologists have extensive knowledge, AI and ML can be helpful companions for healthcare professionals in detecting cardiovascular diseases at early stages and increasing accuracy. Increasing Efficiency One goal for using AI is to achieve quicker diagnoses, and researchers also want to improve the accuracy to enhance treatment. Healthcare experts have begun wielding AI to increase precision when examining patients’ hearts and have seen positive results. For example, Mayo Clinic has an AI-assisted screening tool to detect heart problems without apparent symptoms. This system when finding people at risk with these conditions, improving upon other technologies at the clinic. The medical center says it has also integrated AI with Apple Watch to detect when the user has a weak heart pump. has a 93% accuracy rate Personalizing the Treatment Delivering personalized treatment for patients with cardiovascular issues is essential for care, and AI can build upon this to help cardiologists. AI-assisted technology boosts healthcare providers’ assessment of their patients by analyzing vast amounts of data and painting a comprehensive picture of their needs. With more targeted information, they can understand the nuances of their patients’ conditions and more accurately predict future outcomes. Saving Money Using AI for heart disease detection also means saving money in healthcare costs. Achieving early diagnoses means delivering effective treatments and other mitigation tactics to make the disease more manageable throughout your life. Thus, you’ll save money with fewer complications and hospital visits. This advanced technology also presents opportunities for hospitals to save money by allocating more resources to individuals at high risk for other diseases. Experts anticipate AI to be a significant cost-saving mechanism for healthcare, with an Artificial Intelligence in Healthcare study for America’s medical costs. expecting $150 billion in annual savings Research has already demonstrated AI’s potential to save money in healthcare by reducing the time necessary for cardiologists and their patients. For instance, the AI tool examining MRI scans reduces wait times by about 33% compared to previous technologies and drastically cuts the wait for doctors to check them. The Challenges of AI in Heart Disease Detection While AI has revolutionized healthcare in recent years, it presents challenges for the field that providers must deal with for adequate care. Here are some concerns you may see experts raise with AI and heart disease detection: One criticism of AI is its biases, considering where it sources data. The information may derive from outdated sources built on criticized research, making you question its legitimacy. AI developers must ensure the tools use the best information possible. Biases: While accuracy may increase with AI, there is room for improvement. These tools may accidentally provide false positives or negatives, so healthcare providers must be vigilant and scrutinize the AI’s findings. Accuracy: AI relies on large sets of sensitive medical information, making data privacy a concern for healthcare facilities. Cybercriminals often target hospitals for ransomware attacks due to security vulnerabilities and the amount of information stored in their systems. Privacy: AI Can Detect Cardiovascular Disease Accurately The future of healthcare will depend on AI as researchers develop new tools to assist providers. Some of these technologies have already demonstrated their abilities when studying heart conditions. The past few years have given you a glimpse of AI’s extraordinary potential in healthcare, and the future is bright. While more research is necessary, you’ll see cardiologists and other healthcare providers use AI to deliver more personalized care for you. Lead image by the National Cancer Institute on Unsplash

The is an opinion piece based on the author’s POV and does not necessarily reflect the views of HackerNoon.

AI May Help Detect Signs of Heart Disease at an Earlier Stage

About Author

Comments

TOPICS

THIS ARTICLE WAS FEATURED IN

Related Stories

AI to Become More Integral to Data Center Operations in 2025

100 Days of AI Day 7: Building Your Own ChatGPT with Langchain

100 Days of AI Day 4: Maximizing Productivity & Creativity with ChatGPT

100 Days of AI Day 6: Retrieval Techniques and Their Use Cases

10 Tips to Get the Most out of ChatGPT

100 Days of AI Day 2: Enhancing Prompt Engineering for ChatGPT

AI to Become More Integral to Data Center Operations in 2025

100 Days of AI Day 7: Building Your Own ChatGPT with Langchain

100 Days of AI Day 4: Maximizing Productivity & Creativity with ChatGPT

100 Days of AI Day 6: Retrieval Techniques and Their Use Cases

10 Tips to Get the Most out of ChatGPT

100 Days of AI Day 2: Enhancing Prompt Engineering for ChatGPT

Light-Mode

Classic

Newspaper

Minty

Dark-Mode

Neon Noir

Minty

HN StartUps