AI Healthcare Solutions: Key Use Cases and Highlights for Future

AI in healthcare and its impact are actively discussed by medical experts and software engineers. No wonder that the events dedicated to the AI healthcare role are growing in number.

Thus, the AMIA 2018 Annual Symposium threw light on applying AI to prevent drug diversion, while Stanford University is to hold Machine Learning for Healthcare 2018 and discuss how to turn complex medical data into actionable knowledge using NLP (natural language processing).

But AI in healthcare wasn’t as popular several decades ago.

Dendral was the very first program with a problem-solving feature developed back in the 1960s. It became the basis for MYCIN, the AI healthcare predecessor locating serious bacterial infections. Despite its obvious benefit, MYCIN was never applied. And this happened not because of its bad performance. There was no one to take responsibility for the program failure to make the right diagnosis.

As the years went by, the new theories and approaches were developed. Once intelligent computing appeared, there were a few major improvements made:

• data processing speed-up;
• medical devices and systems improvement;
• genome sequencing databases enrichment;
• artificial intelligence and machine learning technologies further development;

Today, many world-famous AI healthcare companies use this technology for the development of cutting-edge solutions. And the major market players are still very familiar: IBM, Microsoft, and Google. Here is just a quick overview of what they are working on:

• IBM applies AI to create solutions for cancer and chronic diseases treatment as well as for the development of new medications;

• Microsoft conducts in-depth research on how AI can help predict cancer treatment reactions and develops programmable cells;

• Google creates a platform that detects health risks for patients based on the mobile software collected data;

The question is where else AI can be of help in addition to the new drug discoveries? We have listed some widespread applications below.

Machine learning technologies in healthcare use specific algorithms and software tools to reach the human-like cognition. These technologies are further applied to diagnostics and treatments and go farther than that.

• Data Management

AI has powerful capabilities in data processing. That is why researchers think of applying the AI-based software for collecting, managing, and storing clinical trials data. This systematic approach will contribute much to the development of new effective drugs.

• Automation of Processes

Healthcare specialists spend too much time doing routine tasks instead of paying more attention to patients. The AI software can easily handle this monotonous work and manage administrative tasks like training, billing, processing enrollments, and many more.

• Treatment plan design

By analyzing the input data as deeply and thoroughly as no human can, AI healthcare solutions can help create individual treatment plans for every patient.

• Discovering New Medications

Strong analytical features can be used to create new drugs and combine ingredients in the most beneficial way. The drug development can cost a fortune and take years, but with AI it can be less time-consuming and more cost-effective.

• Health Monitoring

Health trackers have gained sky-high popularity. When powered by AI, these devices can turn into good medical assistants by sharing precise reports on patient health indicators.

• Online consultations

By processing a patient medical history and current health condition, AI can provide some basic online consultations or serve as a virtual nurse.

• Genetic-based diagnosis

DNA is a bottomless source of information that may be hard for a human to explore. But a sophisticated AI is powerful enough to analyze the data and predict possible diseases.
This list is not exhaustive, of course. The future will show what other AI applications in healthcare can be in demand, which means that software development outsourcing companies should expand this expertise too.

An idea to create a project based on artificial intelligence development should never be abandoned since these ideas shape our future. Machine learning technologies are already mature enough, so the only remaining question is how to choose a software development company to turn your idea into reality.

When it comes to choosing a healthcare software development company, pay close attention to client testimonials, project portfolio, team qualifications, security policy, and pricing.
In order to save the budget and get excellent service, consider the outsourcing option for implementing artificial intelligence & machine learning projects. Outsourcing companies from Eastern Europe have proven to provide their clients with high-quality solutions. So making the right choice will not take too long.

Artificial intelligence in healthcare has a huge potential to reshape the industry completely. World’s leading healthcare corporations are making their contribution to the development of machine learning technologies that can be used for medical purposes, while startups and outsourcing companies make unbelievable ideas come to life. Hopefully, the big change will come our way soon.