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Industry Insights
Published:
July 7, 2023
Updated:
November 7, 2023

The Role of Artificial Intelligence in Healthcare

Mitha Shameer

The Role of Artificial Intelligence in Healthcare

Published:
July 7, 2023
Updated:
November 7, 2023
Mitha Shameer

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If we were asked a decade ago about all the possibilities of AI today, we would have laughed it off. After all, a machine mimicking human intellect seems like something straight out of science fiction. But here we are today! 

As a patient, you expect to receive quality care and treatment, and rightly so. But patient care goes far beyond rendering an accurate diagnosis and proper treatment. 

Now, you can detect variations in your heartbeat, immediately notifying you of a possible heart attack. A grandmother with Alzheimer's will receive reminders to take medications and even have refills automatically ordered. Booking appointments in convenient time slots without long waiting hours is now possible, thanks to AI.

How healthcare is benefiting from AI

Compared to conventional analytics and clinical decision-making methods, AI has a lot to offer to the world of healthcare. Consumers today have high expectations from their healthcare providers. Whether it is a virtual assistant helping find answers to your common questions or getting personalized medicines by accessing your genetic and personal medical records, artificial intelligence is positioned to be the driving force for breakthroughs across the care continuum.

Below we’ve counted down eight ways artificial intelligence will impact the marketing, delivery, and science of healthcare.

Marketing healthcare products and services

Similar to how language translation bridges the gap between patients and doctors, global brands can also use the same AI technology to market healthcare products and services to consumers across different regions. 

AI-powered marketing tools can assist in creative production by automating creative variations for different products, channels, and regions. This way, more people will have access to healthcare products, making marketing a seamless experience for brands.

AI-driven creative ops tools also use predictive analytics to target the right audience with relevant and personalized ads based on their behavior and preferences. Instead of constantly pushing irrelevant ads to consumers, these marketing strategies benefit brands and consumers in finding relevant ads at the right time. 

Preventative care

One of AI's greatest potential advantages is to keep people healthy, so we don't need doctors as frequently, if at all. People are already benefiting from consumer health applications that use artificial intelligence (AI) and the Internet of Medical Things (IoMT). 

AI-driven healthcare technology with chatbots and virtual assistants supports the proactive maintenance of a healthy lifestyle, including label management. These apps monitor heart rate and sleep patterns through wearable devices and encourage individuals to adopt healthier behaviors, giving us control over our health and well-being.

With AI, doctors can now analyze patient data to identify individuals who are at risk of developing certain diseases and health conditions, enabling them to take targeted interventions and proactive preventive care measures to reduce the likelihood. 

Early disease detection

Researchers are actively investigating the application of predictive analytics to forecast a variety of different diseases and illnesses in addition to heart attacks. For instance: 

  • Based on information buried in mammograms that current clinicians are unable to decipher, AI may detect who is most susceptible to developing breast cancer within the next five years. 
  • AI can identify which individuals at memory care clinics are most at risk of dementia within two years. 
  • AI technology can assist in the early identification of diabetes by spotting hidden correlations in massive patient data sets. 
  • AI algorithms can also predict acute renal injury up to 48 hours in advance.

Additionally, AI improves healthcare workers' capacity to comprehend the regular patterns and requirements of the patients they care for, enabling them to offer superior feedback, direction, and support for maintaining health.

Prompt detection

AI is already being used to more precisely diagnose diseases like cancer. The American Cancer Society claims that a large percentage of mammograms provide misleading results telling one in two healthy women they have cancer. 

Mammogram reviews and translations can now be done 30 times faster and with 99% accuracy thanks to AI, eliminating the need for pointless biopsies.

AI-enabled remote tracking wearables and other medical devices are available to monitor early-stage heart disease. This allows doctors and other caregivers to effectively monitor and identify potentially fatal episodes at earlier, more curable stages.

Decision-making

Decision-making in healthcare requires analyzing large chunks of data to make appropriate and timely decisions. Predictive analytics takes the stress off healthcare professionals in clinical decision-making with greater accuracy. 

  • Healthcare providers utilize pattern recognition to identify individuals at risk of developing or exacerbating conditions due to various factors like lifestyle, environment, genetics, and more. This allows doctors to proactively address issues before they become evident. For instance, AI can provide early warnings to patients prone to seizures or sepsis that otherwise require meticulous analysis of intricate datasets. 
  • Machine learning also assists in decision-making for critically ill patients, including those who have fallen into a coma following a cardiac arrest. By harnessing the capabilities of AI, medical professionals can receive support in deciding whether to continue caring for such patients. 
  • Another critical aspect of patient care involves the examination of EEG data. Typically, healthcare professionals visually inspect this data, which can be time-consuming and subjective. The outcomes may vary depending on the doctor's expertise and experience. AI helps healthcare providers compare results against long-term patterns, revealing modest improvements that could influence care decisions. 

Research 

From research labs to patients, the journey is drawn-out and expensive. A medicine must travel an average of 12 years from the research lab to the patient, according to the California Biomedical Research Association. Of the 5,000 medications that start preclinical testing, only five reach human testing, and only one is ever approved for use in humans. In addition, it will typically cost a business $359 million to produce a new drug from the research lab to the patient.

One of the more recent applications of AI in healthcare is drug discovery. The time it takes for new pharmaceuticals to reach the market and their costs might be drastically reduced by applying the most recent developments in AI to simplify drug research and drug repurposing processes.

Training

AI helps trainees to experience realistic simulations in a way that is not possible with conventional computer-driven algorithms. The development of natural speech and the ability of AI computers to rapidly draw from a vast database of scenarios means that a trainee's response to questions, decisions, or suggestions could be challenging to a degree that a human cannot. Additionally, the training program can take into account the trainee's prior responses, allowing it to continuously modify the tasks to fit their learning requirements. 

Moreover, training can be done anywhere thanks to the power of AI integrated with smartphones, making it possible to do brief catch-up sessions following challenging cases in a clinic or while traveling.

Challenges of AI in healthcare

Although intriguing, the application of Artificial Intelligence in healthcare is not without challenges. AI algorithms hinge on finding patterns in enormous amounts of data. The conclusions drawn from the data will be flawed if they are skewed, inaccurate, unrepresentative of the patient group, or in any way compromised. 

Additionally, it can take a while for hospitals, insurance providers, and the FDA to approve new AI-powered clinical tools even after being fully vetted.

Initiatives utilizing AI in healthcare also need to be aware of ethical issues related to the mining of patient data and practice responsible AI. While AI applications can help recognize patient behavior (such as who is more likely to skip appointments, forego screenings, or reject medicines), they must do so in a manner that protects patient privacy and medical data.

Final thoughts

AI will usher in a new era of clinical excellence and exciting advancements in patient care by powering an advanced generation of tools and systems that make doctors more aware of nuances, more efficient when providing care, and more likely to get ahead of developing problems.

Doctors may now spend less time on administrative tasks and more time getting to know their patients and providing them with the care they need.

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