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Wearables are becoming very popular. A new culture of self-health management is starting to grow as a consequence of the availability of cool devices. People now are aware of their heart rhythms, blood pressure, calorie intake and exercise levels, amongst others. Not only is this a positive cultural change, but it is a great benefit in giving additional care to the elderly. When a device detects health problems it sends an alert to medical staff.

Mobile connectivity allows devices to collect and store large volumes of data. Consequently we can now employ machine learning to analyze the raw data to generate insights. Predictive models can use the data to predict conditions before they become serious.

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Diagnostics and Image Analysis

Diagnosing an illness correctly is fundamental to health care, however, it is often a point of failure. There are many companies building deep learning models that can provide highly accurate diagnoses. These models learn over time and they can compete with human doctors.  The results are likely to improve.

The analysis of x-ray and MRI images is also dramatically improved by artificial intelligence. Firstly, data science is able to clean and enhance the images to help doctors to see the more important aspects of the scan. More recently science has built deep learning models that are able to detect nuances in the image that humans cannot and which can be highly important.

Health Planning

Having data on populations can bring great benefits to governments planning for health care. Areas that have the most need can therefore be prioritized. This is particularly true in the developing world where resources may be more scarce and may need to cover large areas.

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