How AI could transform healthcare in the Mexican state of Jalisco
From：Taiwan Trade Center Mexico
As artificial intelligence is making its presence felt in many business sectors worldwide, some of its applications in Mexico are focused on social healthcare inclusion.
"The state of Jalisco has a very unique AI directorate," Enrique Cortes Rello, CEO of HealthCubed JCSA, told BNamericas. "The mandate is to work on the application of AI to social problems, and the priority is healthcare." Jalisco's AI directorate is an initiative of the state's innovation, science and technology department.
In Mexico, one major problem is chronic diseases such as diabetes and hypertension. "Many Mexicans go years without being diagnosed and they end up receiving medical attention only when they are in a critical phase of suffering," Dr. Liliana Almeida, an endocrinologist and diabetes researcher in Mexico City, told BNamericas. AI is therefore being used to predict healthcare patterns, diagnose diseases, and ultimately aims to lower the cost of healthcare.
Cortes is also working with Jalisco's AI directorate to focus on the problem of diabetic retinopathy, a leading cause of blindness. "This is a well understood problem and there are open datasets."
Barriers to entry
The nature of data is one barrier to the rapid adoption of AI solutions in healthcare, regardless of the country. The requisite data may not exist, it may not apply to a certain group, or it may be so valuable that it is stored away.
From research to startups
The impact felt so far from AI applications in Mexico originates from government centers and universities, as well as from abroad.
While there are dozens of health-tech startups in Mexico City, they tend to serve as platforms for booking doctor's appointments, online health payments and exercise monitoring - so there is a lack of firms looking to make a major healthcare impact.
There is a trend of startups developing chatbots that focus on health advice. One Mexico City-based startup created Yana, a chatbot that speaks with users in order to monitor depression. Such bots are technically driven by rule-based systems that rely on Bayesian statistics, similar to the systems used in robotic process automation but distinct from AI.
AI-powered medical startups may however be just around the corner and they would not be starting from scratch. "There are great frameworks that are relatively easy to use," said Cortes, citing IBM's Watson and Microsoft's Azure machine learning studio.