Different Ways AI Is Impacting Healthcare

Artificial Intelligence (AI) is the theory and development of computer systems or technology that can perform tasks that typically require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages. In healthcare, AI is being used to revolutionize medical care in many ways, from using brain-computer interfaces backed by AI to help patients that can’t speak or move due to neurological disease or traumas to analyzing electronic health record data to identify infection patterns and highlight patients at risk before they begin to show symptoms. In this blog, we focus on how AI technology is expanding in healthcare and its impacts on the healthcare industry. Keep reading below to learn more!

How Does AI Play A Role In Healthcare?

From note-taking to more accurate cancer diagnoses to assisting with imaging scans and automatically analyzing them for various clinical findings, AI and its applications within the healthcare industry have grown and evolved over the years to serve patients better. Incorporating this technology has increased healthcare professionals’ ability to understand patients’ day-to-day needs to provide better care, feedback, guidance, and support.

To do this, AI is being used within healthcare to develop treatment methods, analyze survival rates, and efficiently deliver care to potentially millions of patients regardless of their geographical location or varying health conditions. This type of technology can detect and analyze large and small data trends and make predictions through machine learning designed to identify potential health outcomes. Al also uses statistical techniques to give computer systems the ability to “learn” with incoming data, identify patterns, and make decisions with minimal human direction.

Potential Applications Of AI?

So, what are a few potential applications of AI in a healthcare setting?

Utilize RWD (real-world data) to provide early disease detection and targeted care delivery

Assist in diagnosing patients and treatment

Improve the aging process and quality of life in aging populations

Increase research and training opportunities

RWD generated by wearable health-focused devices such as the Apple Watch and FitBit have significantly improved patient awareness of various healthcare metrics, but what if AI/ML technology can combine this data with patient’s electronic health records to detect potentially life-threatening diseases such as early-stage heart disease? By using this technology application, doctors can monitor and treat potentially life-threatening episodes at earlier, more treatable stages.

As for assisting doctors in diagnosing patients and coming up with treatment plans, technology such as IBM’s Watson for Health helps apply cognitive technology to unlock vast amounts of health data. According to IBM’s website, this technology can review and store medical information ranging from enormous amounts of medical journals, symptoms, and case studies of treatment and responses worldwide exponentially faster than any human.

Google’s DeepMind Health is also doing something similar by working with clinicians, researchers, and patients to solve real-world healthcare problems. The technology combines machine learning and systems neuroscience to build powerful general-purpose learning algorithms into neural networks that mimic the human brain. An increase in the use of these technologies to diagnose and treat patients helps advance the different ways diseases can be treated among patients.

As for helping to improve the aging process and enhancing the quality of life in aging populations, it has been shown that stimulating brain function through music, mental exercises, and activities among older people can help retain their cognitive function for longer. As a result, AI, combined with humanoid design advancements, opens up new doors to utilize this technology to have ‘conversations’ and other social interactions to keep aging minds sharp.

As for research, AI is now being used to improve drug research and discovery by significantly cutting the time it takes for drugs to be put on the market and cutting down drug costs. For example, according to the California Biomedical Research Association, it takes an average of 12 years for a drug to travel from the research lab to the patient. Only five in 5,000 of the drugs that begin preclinical testing ever make it to human testing, and just one of these five is ever approved for human usage. Furthermore, it will cost a company $359 million to develop a new drug from the research lab to the patient on average. Using AI and ML technology to streamline and speed up this process can efficiently treat patients on a faster and larger scale.

Lastly, in terms of training, AI allows doctors and nurses to experience real-life simulations in a way that has never been done before. An AI computer’s ability to instantly draw on an extensive database of scenarios means more training opportunities that can continually be adjusted to meet doctors’ and nurses’ learning needs. Another perk of using this technology is being able to do training exercises anywhere. With the power of AI embedded on a smartphone or a tablet, quick sessions after a case in a clinic or while traveling are now possible where it wasn’t before.

So, How Can BTC Play A Role In This Process?

By working with Boston Technology Corporation, Healthcare organizations can make the most of AI technology to provide patients with high-quality medical care and improve outcomes. To see how BTC can guide you through this process and help you achieve your AI implementation goals, click here.

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