An AI becomes intelligent after it has learned a lot. For example, let’s consider the weather. If a meteorologist considers a number of factors including the size and shape of clouds, temperature, dew point, wind direction and speed, and barometric pressure, he or she can forecast the weather for the next hour will be X. With a different set of conditions, the forecasted weather would be Y. If you applied machine learning software to thousands of conditions and resulting forecasts, an AI could be trained to forecast the weather. As more and more data with sets of conditions and actual weather are accumulated and submitted to machine learning, the accuracy of the forecasts would get better. With enough data and machine learning, the weather AI may produce better forecasts than meteorologists.
Similarly, machine learning can be applied to medical data and enable an AI to learn how to diagnose a medical condition. AI systems are learning to diagnose disease across a wide range of medical conditions, and gradually they are becoming as accurate as human doctors. A good example of AI diagnosing is occurring in London. A collaboration is underway there between researchers from Google’s DeepMind subsidiary, University College London, and Moorfields Private, the private patient division of Moorfields Eye Hospital NHS Foundation Trust.[i] The researchers are using deep learning to create an AI which can identify more than 50 common eye diseases based on thousands of 3D scans. With a single scan of a patient’s eye, the AI can recommend a specific treatment. While the research is still in the early stage, not ready for clinical use, the results to date are very promising. The Verge quoted Dr. Pearse Keane, a consultant ophthalmologist at Moorfields who was involved in the research, saying,
The number of eye scans we’re performing is growing at a pace much faster than human experts are able to interpret them. There is a risk that this may cause delays in the diagnosis and treatment of sight-threatening diseases. If we can diagnose and treat eye conditions early, it gives us the best chance of saving people’s sight. With further research it could lead to greater consistency and quality of care for patients with eye problems in the future.[i]
The software the researchers developed uses algorithms which can identify common patterns in data from 3D scans of patients’ eyes. The scans are made using a technology called optical coherence tomography (OCT). The researchers submitted data from nearly 15,000 OCT scans from 7,500 patients. In addition to the data from the scans, the researchers fed the software diagnoses made by Moorfields doctors. Based on what the AI software learned from the data, it is able to develop a diagnosis a new scan. The Verge reported the AI’s diagnoses were 94% accurate when compared to the diagnoses made by a panel of eight doctors.[ii]
[i] James Vincent, “Deepmind’s AI Can Detect over 50 Eye Diseases as Accurately as a Doctor,” The Verge (2018), https://www.theverge.com/2018/8/13/17670156/deepmind-ai-eye-disease-doctor-moorfields
[ii] Ibid.
