The AI’s usage in Medicine is still very limited these days. Its’ adaptation is a problem and the Healthcare sector has been slow to implement it so far. But that should change.
AI market, according to Frost & Sullivan, “more likely will be grown by 40% in the next 3 years and can potentially decrease the treatments’ costs”. That means some major changes. From cancer and radiology to chronic diseases and surgeries, there are plenty opportunities to use AI in the patients’ care and help people at the right moment.
Firstly, AI offers a lot of benefits over clinical traditional techniques and methods. Healthcare professionals can collect very important information for medical treatments and diagnostics with the usage of learning algorithms and training data. AI can help to evaluate the diagnosis of different diseases, reducing peoples’ errors. It can identify unseen mistakes that can bring new treatments, and analyse the data to provide new insights. Of course, the patients will have the benefits too. With the help of AI, clinicians can do their job more effectively which means that patients can receive better care.
Secondly, one of the biggest AI’s advantage is to help people stay healthy and find the diseases faster with a chance to be cured completely. Plus, it helps the medicine professionals to understand better every individual situation of their patients and to provide better treatment and support. They can have an in-depth approach and be more organized in their care plans and programmes. Healthcare professionals have already used the AI to locate the cancer at early stages faster and with more accuracy which helps to decrease unnecessary biopsies. That completely changes the usage of mammograms in Breast Cancer Sector.
The same situation with early stage heart diseases, which helps to evolve in detecting problems at more treatable stages. Artificial intelligence reduces the risk of patients being undiagnosed or having unnecessary surgeries. AI systems can check the signs of the lung cancer, finding nodules and immediately recognizing them as cancerous or not. Robots in the Healthcare sector can help with surgeries, can work in labs for organizational tasks, as well as, in rehabilitation and different types of therapies.
On the other hand, the Healthcare sector is spending enormous amount of money on the customer services. Most of it goes for paying the service representatives, who take patients’ inquiries through the live chats, via emails and on the phone. It means that, it’s another area where robots can help to decrease the costs and make the service more effective. Unfortunately, they can’t handle emotionally complicated tasks yet. It will take some time for them be able to empathize as humans. Once the developers will achieve the necessary emotional intelligence in chatbots, customer service is possible to become completely automated.
So another area is the drug research and its’ implementation in people’s lives. The way from the Research Lab to the patient is very expensive and long. The discovery of the new drug, its’ testing and production is very important that’s why the AI is taking this responsibility as well.
A huge advantage that we can store the healthcare data in different formats, such as text, audio, scans, numbers, pictures and video. There are many examples that demonstrate success in using AI with different types of data. For example, the healthcare professionals can use the AI models to analyse MRI scans, measure the growth of tumour and help with the patient’s care decision. We can process the text type data as well. According to the medical test results which have been already done “on 8500 patients, these people were tested to the risk of heart failure, with the precision of 85%, with the help of a neural network. And with the precision of 100%, the medical workers used another technique to identify psychosis in patients with schizophrenia”.
There are some problems that we still need to resolve in terms of implementing AI in the Healthcare sector but also some examples of how artificial intelligence has been already used.
- The sensitivity of patients’ medical data, its’ access and usage
- The difficulty of accepting the AI technology in our daily life
- The lack of knowledge about AI in general
In order to resolve these problems, there should be a very productive cooperation between data scientists and the healthcare sector.
Here are a few examples of how AI has been already implemented in the Medicine:
- Virtual assistants in helping patients and clinicians
- Smart robots that explain lab reports
- Improving clinical documentation
- Healthcare monitoring devices
- Help in tuberculosis detection
- Aging-based AI centers
- Personalized medicine
- Verifying insurance
- Robotic surgery
- Drug discovery
- AI chatbots
On the other hand, there is still a controversy over this topic as AI involves the usage of patients’ data which might be problematic. But even being imperfect, the AI technologies in the Healthcare sector procure the bright future.
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