We are using Artificial Intelligence (AI) a lot now, especially in hospitals. AI helps do jobs faster and keeps track of patients and hospital tools better.
Most of the work that people used to do, AI can do it quicker and for less money. This makes things easier for everyone in hospitals, like the head of the hospital, doctors, and even the patients.
A recent study by Tractica said that by 2025, AI in healthcare could make about $8.6 billion a year from 22 tools. People also guess that by the same year, AI could bring in $34 billion globally.
AI keeps getting better and smarter. Now, there are new AI tools that can act, learn, and predict things. These tools can do more than the older ones, which just helped in surgeries or looked at genes.
But using AI in hospitals is not without problems. For example, if AI makes a mistake, a patient could get hurt. And using patient data can risk their privacy.
This article talks about the good things AI can bring, but also the challenges and possible problems. Let's first talk about the good parts.
Many countries that are not very advanced have trouble getting good healthcare. This means people in these places have a higher chance of getting sick or dying early. In fact, the World Health Organization (WHO) says that the difference in how long people live between the richest and poorest countries is about 18.1 years. This big difference is because of not having good healthcare.
But with AI, these places can have better healthcare. AI can help doctors figure out what's wrong with a patient and how to treat them. There are special computer programs that let health groups from around the world work together to help these people. This means even if a place doesn't have many doctors or hospitals, AI can still help them get the care they need.
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Using Artificial Intelligence (AI) in healthcare makes sharing info a breeze. For AI to work best, it needs to look at a lot of data quickly.
AI can find patient info faster than the usual ways, which lets doctors focus more on giving the right medicine and treatments.
If someone needs quick treatment, AI can give doctors the info they need. Like, there's a system that lets people with diabetes see their sugar levels right away. They can then share this with their doctor or group to see how they're doing.
People can also wear devices that use AI to show if they might get a certain sickness. As healthcare uses AI more, we'll have a big pool of data that could help us understand and treat diseases better.
AI tools now use people's health data to look at past and current health problems. By looking at this data, doctors can be more sure about what's wrong. Many health apps have a lot of information on symptoms and what they might mean. The cool thing is, these tools can even guess what health problems someone might have in the future.
For example, there's an app by Google called Verily. It's made to guess if someone might get certain genetic diseases. With tools like this, doctors can guess what health problems might come up later and do something about it now. This also helps hospitals run better because they can plan ahead.
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Thanks to AI, healthcare is now quicker and cheaper. From checking patients to finding out what's wrong, AI has made things much faster and less expensive. For example, AI can spot signs of disease in our bodies. With AI, there's less manual work in finding these signs. Because of this automation, we can help people faster, saving more lives.
Using AI is also more pocket-friendly than old methods. People don't need to visit the lab as often because AI can guess the results using their personal info. This is why so many places have started using AI in healthcare. In fact, in the last year alone, 88% more places started using it.
Often, hospitals can be very busy and confusing.
But with AI, patients can easily get information, reports, and know where to go or who to talk to. This helps avoid the usual mix-ups in hospitals. In fact, a study showed that 83% of patients said bad communication was the worst part of their hospital visit.
Another cool thing about AI is that it's always available. A great example of this is an app called Babylon. It acts like a smart symptom-checker. The app asks you questions, you give answers, and it checks those against known symptoms and risks to give up-to-date medical info. This helps patients a lot.
Thanks to AI, we now have robots that can help in surgeries.
These robots can make super precise moves without any mistakes. This means they can help doctors do complicated surgeries more safely. Patients bleed less, hurt less, and heal quicker after surgery.
For example, before surgery, some patients get tiny robots in their blood to kill infections.
The best part is that doctors can see live info about the patient during surgery because of AI. This makes patients feel safer, especially if they're asleep during the surgery.
Robots aren't just for surgeries. They can also help people in everyday life. Some robots, like exoskeletons, help people who can't move to walk again. There are also smart fake limbs that work even better than old ones because they have sensors.
Some robots can do daily tasks and spend time with patients.
They can check things like blood sugar, blood pressure, and even remind patients to take medicine. Some robots are made to talk to people who feel sad or down. They can understand how a person feels and try to make them happier.
Everything has its good and bad sides. The same goes for using AI in healthcare. Even though AI has brought a lot of good changes, there are still some problems, especially with data. For AI and machine learning to work best, we have to tackle issues like:
Having good data is key for AI. If you put bad data into AI, you get bad results out. For AI to help in healthcare, it needs a lot of good quality data. But getting this data can be hard. Why? Because health data is spread out everywhere and is not always organized. Think about it: people often change doctors or insurance, so their data is all over the place.
In some countries, it's even harder to put this data together because their data systems are old or not connected. In the US, they're trying to make all medical data digital, but it's still not perfect. For instance, eClinicalWorks, a big software company that keeps medical records, had issues that could hurt patients.
If we can get all health data in one digital place and make sure it's accurate, healthcare can be better and safer. That's why it's important for healthcare experts to focus on making sure medical data is both digital and organized. Only then can AI use this data to help people the best way.
Most doctors don't really know a lot about AI. AI systems work kind of like our brains, which means it's hard to understand how they make decisions. This is called the "black box" problem: stuff goes into the AI and an answer comes out, but we're not sure what happens in the middle.
This can be risky in healthcare. If a doctor doesn't know why AI suggests a certain treatment, it might be dangerous. So, right now, it's super important that AI tools are used together with expert doctors. These doctors can double-check what AI suggests.
Also, for a hospital or clinic to use AI well, they need experts who know both healthcare and AI. This is tricky because there aren't many people who are experts in both these fields. Data science, where AI comes from, is still a growing field.
Medical records are very private. There are many laws around the world to keep them safe. But, if we want to share data with AI systems, sometimes it might break these laws. Even if it's allowed, patients need to say it's okay to use their data.
This creates big challenges. We need rules that let us use medical data in AI while keeping people's identities safe. Hospitals and clinics must follow these rules very carefully. They should also be responsible for how they get and use patient data. This is important for AI to have good and safe data to work with.
Many people are still unsure about AI. Some doctors, like those who take X-rays, worry that robots might replace them. Patients are also nervous about trusting machines with their health.
Remember when the pandemic started in 2020, and we began having doctor appointments over video? A lot of people were unsure about it. They wondered how a doctor could check their health without being in the same room. But when patients learn that surgery with robots might mean smaller scars, less bleeding, and faster healing, they might start to like the idea of AI in healthcare.
To make AI work in healthcare, we need to help patients understand it better. AI isn't trying to replace doctors; it's here to help them do their job better. When people understand and trust this, they'll be more open to using AI in their medical care.