Despite a long history of development, artificial intelligence (computers and programs that can think, learn, and behave in ways that are indistinguishable from humans) has seemingly appeared in the public awareness overnight. AIs are everywhere, answering our customer service questions, predicting the weather, and sharing data with unprecedented speed, accuracy, and usability.

Today, the public routinely interacts with artificial intelligence (AI), often without even realizing it. Apple’s Siri and Amazon’s Alexa are two examples of AI that have found widespread use in the mainstream.

AIs are being used for everything from data analysis, pattern recognition, design efficiency, administrative support, and more. As tools, AIs are being leveraged for roles in virtually every industry, including healthcare.

AIs Are Changing Healthcare for the Better

Healthcare field is vast, complex, and challenging field. Research review in particular has become almost unmanageable for the average caregiver due to the enormous amount of data and studies available.

For healthcare professionals, being able to synthesize all this information for effective use in clinical settings has become more a challenge. AI researchers are overcoming that barrier with new ways for addressing diagnosis and treatment of disease.

AI Diagnostic Tools May Improve Diagnoses

Pathology, for example, is benefiting from pattern recognition programs. Similar to Apple’s facial recognition software that can identify unique facial features, pattern recognition operates by examining tissue sample to identify cells.

In April 2017, the Food and Drug Administration (FDA) approved the first whole-slide imaging system for digital pathology. With resolutions of up to 400 times magnification, pathologists can now examine even the smallest of samples. As a storage system, pathologists around the world will have access to thousands of images for comparative purposes that otherwise would be buried in inaccessible physical files.

With this ability for large storage capability, the next step for AIs is to take on the actual diagnosis of cellular disease. Recently, Google demonstrated an AI program that performs with accuracy rates in detecting cancer metastases as well or even better than human clinicians.

In one study of breast cancer cells, the AI system had an accuracy rate of 89% compared to the human rate of 73%. Since by some estimates pathology serves as the basis of up to 80% of medical care, the ramifications for improving care are significant. AI could even drastically decrease the occurrence of medical lawsuits that result from misdiagnosis.

AI Predictive Capabilities Can Inform Effective Strategies

Epidemiology is another area of medicine perfectly suited to AI support. Inherently a study of data, epidemiology can benefit from AI algorithms that look for data patterns across populations to assist in diagnosis and treatment.

These algorithms could also be used to predict potential outbreaks. A company called AIME (Artificial Intelligence in Medical Epidemiology) has been focused on precisely these issues. They have successfully developed an AI algorithm, for instance, that can predict outbreaks of Dengue fever with 87% accuracy.

Using a combination of seemingly random data points like construction activity and weather patterns, an AI algorithm can bring computational power to produce insights from data that might be missed otherwise. Armed with data that has proved demonstrably accurate, governments and the medical community can provide services and treatments more quickly and efficiently to avoid matters becoming worse.

The AI Market Will Continue to Expand

By 2027, analysts believe the current AI investment market of $5 billion will increase to $139 billion. As the tools and applications of AI spread, physicians will be able to deliver highly personalized treatment based on a solid data.

Sophisticated data-sharing techniques will eliminate the need for redundant studies across borders, deliver real-time diagnosis and treatment anywhere in the world, and reduce overall healthcare expenditure costs while improving outcomes.

These benefits are based on current knowledge of the potential AI offers healthcare. As the systems become more refined and nuanced, the AIs themselves may eventually be able to offer significant contributions to medicine that humans have not yet imagined.