thousands of X-ray and MRI images looking for tiny, subtle details on each photo. It’s an almost impossible task. And missing an important detail could mean the difference between life and death. Statistics show that they only get it right about 70% of the time. In 2011, engineer Krista Jones found a lump in her breast. She had to rely on human analysis to treat her rare kind of cancer. She went through four years of scans, ultrasounds, biopsies, and surgeries. It seemed that a double mastectomy was the only answer for her. That is, until 2015, when she found a doctor who took a different approach. He used big data and machine learning to spot her tumors and treat them directly with radiation therapy. This plan of attack not only stopped her tumor growth but has also kept her cancer- free since August of last year. We love stories about people beating this awful and deadly disease. It proves that technology is literally saving lives. And no one can say it better than Krista herself in an article from Quartz... I was thankful for the A.I. that saved my life. When it comes to diagnosis and treatment, A.I. will radically improve the quality of treatment for patients... and the productivity of doctors. In other words, it will make doctors better at saving lives. Machine learning, deep (machine) learning, and artificial intelligence are intertwined fields of computer science. Both machine learning
and deep learning teach computers to think like humans. This is the technology that helps with tasks like speech-to-text on your smartphone or image recognition in your
online photo album. Machine- and deep- learning technologies allow software to adjust and improve over time by using
ARTIFICIAL INTELLIGENCE
MACHINE LEARNING
large training datasets. The
training data allow the software to learn context, so that it has a basis to learn. It’s the same learning process a person goes through when he learns something new. And
DEEP (MACHINE) LEARNING
for radiologists, this is great news. A.I. will allow their software to identify abnormalities in CT and MRI scans that are too small to spot with the human eye. As we said earlier, the A.I. business is growing at an exponential rate. It’s all part of Big Data. Research firm McKinsey estimates that Big Data, which includes machine learning, and analytics will become a $100-billion-a- year business in earnings before interest, taxes, depreciation, and amortization (EBITDA). That offers huge upside.
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