How AI Is Changing The Healthcare System

Improved doctors’ training

Medical training is so complex that it can take up to 10 or more years. This is because medicine is a science that accumulates centuries of discoveries and technological advances. Our broad knowledge of the human body allows us to understand and treat many diseases. But, at the same time, it requires a great deal of knowledge that can only be accumulated through many years of study. This and other factors are leading us to a considerable shortage of medical personnel. Could artificial intelligence help us solve this problem?

Training

Artificial intelligence and machine learning could have several applications in medical training. One of them regards interactive real-life simulations. Imagine: people studying to become doctors or nurses learn the complex anatomy of the human body on 2D anatomical pictures (and on bodies donated to medical science). With the use of digital simulations, they could see functioning body parts in 3D. They could interact with them and see their reactions, recreated by drawing information from the AI’s large database of scenarios. They could learn from making mistakes without real life consequences. The AI-powered simulated training could adjust to the student’s knowledge, adjusting the challenges according to the learning needs. Finally, students could train from anywhere and at any time.

Drug Research

The use of artificial intelligence could also help doctors have better drugs to treat their patients with. As we probably have noticed with the recent pandemic, it may take years to create a drug or vaccine that meets a medical need. On average, it may take from 10 to 15 years for a drug to go from a lab to pharmacy.

  • AI can predict potentially effective molecules with more accuracy, saving time and money usually spent on compounds that end up being ineffective.
  • It can also suggest compounds itself, after predicting tha they have all the desired properties required for success.
  • Finally, AI can take care of many repetitive tasks that usually require several hours to be done.

Improved patient care

Not only can artificial intelligence help doctors do their job in an easier and more effective way, it is also beneficial from a patient’s perspective. More accessibility, more education, more personalisation — there is a lot to gain out of these future technologies.

Education

Chronic diseases (such as heart diseases, cancer or diabetes) have many causes and we don’t know yet how we can completely avoid them. Yet, there are some behaviours we can adopt that lower the risks. Artificial intelligence could suggest personalized behavioural adaptations by comparing changes in our vital parameters with a wide database of diseases history. In the future, we may be able to have a personal virtual assistant checking on us and keeping us well.

End of life care

Since living standards have been steadily improving, we live much longer than the previous generations and we suffer more often of diseases connected to aging: dementia, heart failure, osteoporosis. In England for example, the most common age of death is 85 years old. This should make us reflect on the importance of institutions and systems for the care of the elderly.

Improved treatment of diseases

Another essential field in which artificial intelligence could make a difference in the years to come is the detection and therefore prompt treatment of diseases.

Early detection & diagnostic

One of the aspects of the healthcare system where artificial intelligence is being used the most nowadays is definitely disease detection and diagnosis. AI is very accurate where the human eye can be sometimes fallible. Let’s have a look at three examples.

Treatment

After helping to detect a disease, artificial intelligence can help treat it. Through computational models and machine learning, AI can assist doctors in deciding the best course of treatment. For example, for patients with cancer, researchers can use predictive analytics to determine how an individual will respond to a certain treatment. Not every patient has the same response to medications. Predictive analysis can avoid patients going through a cancer treatment (with its side effects) that may not work for them.

  • Preoperative phase: AI can provide real-time analysis of a patient’s data combined with their clinical history, and assess a specific risk score. The surgeons can use this data as a tool for decision making.
  • Intraoperative phase: AI can monitor real-time data to predict and avoid adverse events.
  • Postoperative phase: AI can monitor recovery and predict possible complications.

Conclusion

Artificial intelligence applied to medicine is changing not only the work of medical professionals but also our relationship with health in general. We expect a future in which AI will work alongside doctors, enabling them to do their jobs better and save more lives. A future in which we will be healthier and live longer.

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