The Rise of AI and Machine Learning in Healthcare

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The Rise of AI and Machine Learning in Healthcare

As healthcare grows less centralized, providers and clinicians must reconsider how to treat patients from afar. There is still a great demand for in-person treatment, but remote care has soared in popularity since the pandemic. The convenience, accessibility, and often affordability of these services make them a great option for many.

At the forefront of this new wave are AI and machine learning, hand-in-hand innovations that are changing the face of healthcare. However, they can be complex topics, so it helps to know the basics.

How Machine-Learning Healthcare Serves Patients Differently

Before 2020, healthcare was primarily delegated to the provider. Outside of some telehealth and remote options, receiving care meant going to a physical location. Additionally, the treatment could sometimes be homogenized to handle the demand.

In contrast, AI healthcare seeks to use pre-existing data to inform and adapt to patients’ needs. This coincides with a greater movement of focusing on patients first by listening to their expectations and concerns from the very start. While many other industries have adopted this approach, healthcare is only beginning to make this shift. Thomas Swanson of Adobe’s Health and Life Sciences team says, “As consumers in all other industries, we have built expectations as to what digital experiences look and feel like… And what degrees of personalization we expect as a result of that data.”

The digital experience for patients is paramount to the future success of AI healthcare. It is an opportunity for personalization, but it’s also the greatest barrier to adoption among patients. Al Zinkand of Baylor Scott & White Health observes that “our doctors have trust, the systems often do not.” The unique intersection of commerce and health means providers need to improve both aspects simultaneously. As Al notes, this requires “meeting [consumers] in their emotional state through technology.” If executed well, machine learning can be a permanent and effective alternative to physical office spaces.

Health Management and Sick Treatment

AI can also adapt to another change in the healthcare landscape: personal care management. Many patients are resisting the current model of treatment where care is only given when required. Instead, people are looking to manage and improve their health consistently. AI and machine learning can cater to this desire by being far more accessible than the average doctor. They can also utilize greater data sets to make accurate recommendations, refer resources, and accommodate requests quickly.

Tom Hileman of Hileman Group sees the potential of AI to meet the wants of the emerging generation, saying, “they want convenience; they want price transparency; they want to be able to schedule an appointment and take care of their health…And I think that’s what we have to think about in healthcare marketing is ‘where do we create value in their minds and how do we apply it?’” All of this is much easier when it does not require the constant attention of busy doctors and professionals.

How Does This Differ From Chatbots?

Many consumers are wary of AI healthcare options because of previous experiences with chatbots. These tools had value but were lacking in many areas. Not only were they inflexible, but they often failed to provide meaningful solutions to struggling patients. While AI solutions will never replace human care, they are a far improvement.

AI platforms today are rooted in deep datasets, growing more refined every day. They are built on knowledge from doctors and medical professionals to give genuine insight into the patient’s condition. According to Chris Hemphill of Woebot Health, his company conducted a study into the relationships between AI and patients and “found that people were forming similar human life bonds with the AI that they’re talking to within two to three days.” This model can also avoid some of the biases found in humans, focusing on holistic health from multiple sources from an objective perspective.

The future of healthcare can be daunting, but there are also many developments to consider. AI and machine learning are quickly growing to meet patients’ needs, finding modern solutions in a post-pandemic world. While there is a lot of work left to be done, it’s a promising start for burgeoning healthcare technology.


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