Computer have wide applications across industries for quality control.

For instance, the majority of all medical data is image-based: The assessment of X-rays and scans is crucial for the right diagnosis and, thus, for the right treatment.

Public health depends on the accurate interpretation of every single image, and many physicians are obliged to choose between longer working hours or doing less detailed and precise medical image analysis.

Right now, medical staffers around the world are stretched thin, this is where AI can come into play.

Artificial intelligence in healthcare speeds up the process of medical image analysis and makes it more accurate and stress-free for medical personnel. Using artificial intelligence, it is possible to detect rare diseases, such as Noonan syndrome, or identify viruses and bacteria by analyzing Petri dish images. Computer vision and machine learning for medical image analysis are becoming as vital as an experienced lab worker with modern equipment.

Every once in a while, I get asked “I get why analytics is so important to the enterprise, but what can you really do with computer vision?”

Here’s a great example of a company using computer vision for quality control.

Pleora Technologies introduced what they deem the vision industry’s first artificial intelligence (AI) platform that simplifies the deployment of advanced machine learning capabilities to improve quality inspection.