Abu Qader, 18, came to the U.S. from Afghanistan as a baby. Now a freshman at Cornell University, he has founded a medical technology company with the goal of improving diagnosis of breast cancer in poor countries. Abu Qader, 18, came to the U.S. from Afghanistan as a baby. Now a freshman at Cornell University, he has founded a medical technology company with the goal of improving diagnosis of breast cancer in poor countries. After a family trip to Afghanistan when he was 15, Chicagoan Abu Qader decided he wanted to do something to improve the country's medical care.

By 2020, the market for machine-learning applications will reach 40 billion, per IDC. The next time you see Democratic presidential nominee Hillary Clinton with an unflattering look on her face in a TV spot supporting GOP rival Donald Trump, it's all but certain you can attribute the ad creative to artificial intelligence. The Republican National Committee is using machine-learning software from Veritone, a 2-year-old player that just secured 50 million in funding. Designed to work with laser-fast precision, its audio-based system lets the RNC zip through all the publicly available times Clinton has spoken on TV, radio or online video to scoop up her angriest or oddest moments. The company is about to add a visual-sentiment feature, which will zero in on facial expressions and make cringe-worthy moments even easier to find.

How much can a 17-year-old boy really know about women? For starters, that thousands face heartbreaking and costly misdiagnosed breast cancer scares every year. Abu Qader, who's about to start his final year in the Chicago public school system's Lane Technical College Prep High School, was born in war-scarred Afghanistan but has spent most of his 17 years on Earth in the U.S. Qader and European business partner Vedad Mesanovic, who focuses on young and under-resourced scientists, created a company they call GliaLab (named after the cells that support and protect neurons). They are now courting venture capitalists for a targeted 600,000 to help finance the breast cancer-focused artificial intelligence that Qader first created for a 10th-grade class project. Qader believes his technology can help women (and men, too) take on potentially deadly breast tumors and non-cancerous growths by using the convenience of their own mobile phone or tablet to aid in diagnosis and classification, reduce human error and save the expense of false-positive readings.

About 12% of women in the US will develop invasive breast cancer over the course of their lifetime, and there are expected to be close to 250,000 new cases of breast cancer in 2016 alone. With a breast cancer diagnosis comes fear, anxiety, stress, added expenses and--sometimes--a missed diagnosis. Approximately 5% to 17% of breast cancers are missed by a radiologist. Mammograms can also result in a false positive or an overdiagnosis, which leads to additional and unnecessary cancer treatment for the patient. According to a study by Health Affairs, between 22% and 31% of all diagnosed breast cancers are overdiagnosed, resulting in an additional 4 billion in health-care spending annually.