AI has already made an incredible impact on most of our daily lives as it continues to seamlessly integrate with all of our daily functions.
The next sector that AI is affecting in a meaningful way is the future of healthcare which has seen rapid change and momentous shifts.
AI has already impacted research and analysis so greatly that it has already produced a few cures and solutions. However, AI has also affected the creation of pharmaceutical drugs and impacted when and how they are created.
Research and development
With every new technology, we are given new opportunities to blaze a new path as well as retread old ones with a new perspective. AI can help pharmaceutical researchers tackle new problems as well as revisit old ones.
Drug trials are often a long and laborious affair. Research and development can take years, even decades under certain conditions. Worse still, drug makers work to appease queasy investors looking for a gigantic return in a volatile but profitable industry.
These drugs are typically created and produced through drug trials with willing participants. These trials usually cost a ton of money to perform and still yield limited results that must be used to generalize effects. Instead, these drug companies can use AI to quickly analyze and understand decades’ worth of drug trials and other information to gain a much better understanding of what they are making and how it will affect users.
Medical trial analysis
Simulating medical trials as well as potential chemical compounds and the like can make drug creation and test much more efficient. For a risk-averse industry plagued with the highest highs and the lowest lows, AI-assisted simulation and analysis of drug development and drug testing is a sorely needed technology.
Education and training
Education and training are some of the most under-appreciated applications of machine learning. While education is often a hotly debated topic, whether it pertains to learning content or budgetary policies, public education is juggled between indifferent bureaucrats and self-interested companies.
All said it’s a rather tangled mess. As such AI technologies are needed to help reshape how students learn the art of medicine. Medical students can leverage AI to help them simulate real-world experiences, run test cases, and participate in AI-assisted AR and VR training sets.
Mental health
Mental health is often avoided. Insurance companies don’t like to cover it, people don’t want to talk about it, and health providers have trouble treating it. Artificial intelligence is helping address mental illness, however. Mood tracking apps, real-time analytics, and AI-assisted brain imaging are just some of the AI applications related to mental health.
Also, AI apps can help those suffering from chronic mental illness to analyze and manage their health data as well as give them personalized management strategies as well as virtual nurses and medical assistants.
AI can be used to randomly sort and execute drug trials which yield great results and provide in-depth information. This same AI can then analyze the data produced and create complex data sheets that document the process and clarify the results. Training medical students and pharmacists are also a costly endeavor for both the students and the educator but with the help of AI, most of the burden can be alleviated. Medical students use AI to help with research, assist in experiments, and collect data on a massive scale.
Telehealth is also used to see patients and also to see other students who wish to be medical professionals. This is all accomplished through a series of AI that manages bandwidth and internet access to provide a seamless interactive experience. Additionally, students and professionals can use telehealth to interact perform group activities or use mixed reality simultaneously.
However, AI has also been used in a much more direct way by assisting surgeons in real-time through data analysis and medical organization. AI can quickly compile data on a patient and determine which course of action would be best suited to the individual patient. Overall, these technologies amount to an AI system that is comprehensive and complex, capable of training students and changing lives.
Romy Catauta works at Toptal in the marketing field and is passionate about writing on web design, business, interior design and psychology.
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It seems to me that machine learning is really our future. It was clear even when it first appeared. I was trained in machine learning, and honestly, I still can’t figure out why all companies don’t make machine learning-based robots for themselves, and don’t start filling the market with them. It’s much more profitable than hiring people) But the truth is then people will not have a job, which is sad ((Thanks for the interesting article!
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