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artificial intelligence

A Closer Look at the Potential of Artificial Intelligence in Healthcare

artificial intelligence

As artificial intelligence (AI) becomes more advanced, it’ll continue to impact all different types of sectors, from finance to marketing to hospitality. One of the industries that stands to gain the most from AI is healthcare.

With about 10,000 Baby Boomers turning 65 every day, there will be about 95 million seniors in the U.S. by 2060 – almost twice as many as 2018. Experts also anticipate a shortage of as many as 104,900 doctors by 2030. Considering these expectations – a rapidly aging population combined with a lack of physicians – the need for assistive healthcare technology will only become more important in the future.

So how can we use AI to meet the needs of our changing healthcare system? Here are three ways it can help patients and providers:

More accurate patient assessments

Artificial intelligence can help cut down on the time and effort it takes for providers to evaluate patients’ care requirements — especially during emergencies. With AI, providers will be able to perform fast, comprehensive patient assessments to give patients the care they need more quickly. This not only saves time, but also helps eradicate medical mistakes made because of human error.

Personalized treatment plans

With advanced AI, providers can analyze patients’ genome to formulate personalized treatment plans that fit their unique genetic makeup. This type of precision medicine is becoming especially useful in treating cancer, which is often rooted in genetic instability. AI can also use data on patient symptoms, location, and lifestyle to develop a more customized treatment approach.

Drug discovery

Pharmaceutical companies are using AI to process huge quantities of research and patient data, which is now accessible thanks to the digitization of medical records. This type of macro-scale analysis, also called “deep learning”, trains complex neural networks to recognize patterns in order to spot promising therapies. The same approach may also help identify ineffective drugs sooner, before companies overspend on a poorly performing product.

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