The launch of ChatGPT has changed the way we think about artificial intelligence (AI) and made clear how powerful modern AI systems are.
The implications for the new generative AI tools are vast, and they could disrupt a wide range of industries, including education, media, law, design, software programming, and more.
One of those industries ripe for disruption from AI is healthcare, and tech titans like IBM (IBM 1.05%) and others have already been applying a wide range of artificial intelligence and machine learning tools to things like improving diagnostics and patient outcomes and making healthcare more efficient.
In this discussion of artificial intelligence in healthcare, we'll examine where AI is today and then explore several of the top uses for AI in healthcare.
Understanding artificial intelligence
Understanding artificial intelligence
AI is generally understood as the ability of computers and machines to do tasks that normally require human intelligence.
Typically, the type of training involved falls under the umbrella of machine learning, or training computers so that they improve at a given task as they get more feedback. One example is Meta Platforms (META -0.52%), which uses AI to screen images and texts for banned or inappropriate content. As the algorithm learns more about what social media content is desirable and what isn't, it gets better at selecting appropriate posts.
Another example is Netflix (NFLX -3.92%), which uses AI for personalized recommendations, giving viewers individualized recommendations based on their past viewing history and movie ratings.
In healthcare, AI is used for a variety of functions, including diagnostics and early detection, as well as drug discovery in pharmaceuticals and developing treatment plans for patients. It's also used to improve patient outcomes in other ways.
1. Precision medicine
1. Precision medicine
One application of machine learning in healthcare is precision medicine. In precision medicine, AI is used to help predict the treatment regimens that work best for individual patients based on their medical histories.
Treatments are customized for an individual patient rather than just being based on large-scale data, and it uses AI for genomics, predictive modeling, and diagnostic decision making. Precision medicine also uses natural language processing, another form of AI, to make sense of a broad range of data inputs, including clinical notes, blood tests, and drug responses.
Among the companies known for precision medicine are Roche (RHHBY -2.24%), Novartis (NVS 1.1%), and Johnson & Johnson (JNJ -0.69%). Johnson & Johnson, for example, has collaborated with Rest Devices to develop apps that track babies' sleeping habits and give them wearable tech that tracks health signals like body temperature and breathing.
2. Drug discovery
2. Drug discovery
Drug discovery is another common way that AI is used in modern medicine. Today, a number of biotech companies are using AI to help streamline the drug discovery process and improve existing drugs.
Drug development yields large data sets, which AI can help process, and AI can help identify and refine the target of the drug to make it more effective.
It can also help researchers scan through available compounds to see what would work best to fight a particular disease, and AI can assist during clinical trials by analyzing patient data and predicting outcomes based on different dosages and treatments.
One example of a company that is using AI for drug discovery is Bayer (BAYR.Y -1.49%), which has partnered with Exscientia (EXAI -5.71%) to use an AI-based algorithm to predict potential drug molecules. Exscientia is also using its AI drug discovery platform to create oncology candidates with Roche.
3. Medical diagnostics
3. Medical diagnostics
Perhaps the most direct application of AI in healthcare is with medical diagnostics. AI-powered software can analyze MRI and CT scans in real time, speeding up important patient feedback and helping doctors make better diagnoses.
Identifying patterns is also key to early diagnosis of some diseases. AI can find patterns in patient data and genomes that could indicate that a disease is present. For example, Arterys has used AI to improve diagnoses of heart defects in newborns and children. The company designed a system that used deep-learning, cloud-computing graphics processing units to automatically measure ventricles, saving radiologists time and getting the information they need faster.
Demand for medical imaging diagnostics has become particularly acute, increasing by more than tenfold at the Mayo Clinic from 1999 to 2010, going from 9 million to 94 million images, according to IBM. The number of images that required interpretation exceeded the number of radiologists available.
By interpreting those images, AI could help free up radiologists and other doctors to do work that must be done by humans, improving care for patients as well.
4. Robotics
4. Robotics
Robotics may be the most vivid representation of artificial intelligence right now.
Today, industrial robots have become common, often doing basic jobs like moving shelves. However, surgical robots have become more commonplace in the U.S. since they were approved in 2000. Surgical robots help improve surgeons' ability to see and do precise, minimally invasive incisions, apply stitches, and handle similar duties. Surgical robots are now commonly used in gynecologic surgery, prostate surgery, and head and neck surgery.
Companies like Medtronic (MDT -1.12%) and Intuitive Surgical (ISRG -0.55%) make surgical robots that are used for procedures in areas like gynecology, urology, and general surgery. In 2021, Medtronic performed its first procedure, a minimally invasive prostatectomy.
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Is artificial intelligence the future of healthcare?
There's no question that healthcare is one of the many fields being transformed by artificial intelligence, and the implications for AI in the medical field are enormous.
Potentially, AI can help bring prices down for medical care by replacing human beings with machines in areas like robotics or in medical imaging analysis.
AI should also help improve patient outcomes by making inferences that a human doctor might miss or recommending treatment plans. AI also has the ability to follow up with the patients to make sure they are following the treatment plan as prescribed.
Drug discovery also seems like an area where AI could unlock a lot of benefits as drug researchers deal with large amounts of data, and artificial intelligence has the ability to generate insights from it that humans might miss.
There will always be a need for humans in medical care, of course, but investors should expect applications of AI in healthcare to continue to improve and proliferate as the underlying technology gets better and patients and doctors begin to welcome the assistance.
With its ability to both cut costs and improve outcomes, the benefits of AI in healthcare are clear. Investors looking to take advantage of the opportunity should consider investing in AI stocks and ETFs or healthcare stocks since many of them are already working with AI technologies.
