The use of artificial intelligence in medicine is growing rapidly.Credit: ktsimage/Getty Each day, around 350 people in the United States die from lung cancer. Many of those deaths could be prevented by screening with low-dose computed tomography (CT) scans. But scanning millions of people would produce millions of images, and there aren't enough radiologists to do the work. Even if there were, specialists regularly disagree about whether images show cancer or not. The 2017 Kaggle Data Science Bowl set out to test whether machine-learning algorithms could fill the gap.

To find the cure for any disease, researchers analyze how the cells of a sample react to various treatments and understand the underlying biological processes. Identifying the cells’ nuclei is the starting point for...

Most of us love a good chocolate brownie. The existence of chocolate is not the only reason. We also love a good brownie because of its texture, convenient serving size, the presence of nuts (or other confections), and its "just right" density (otherwise, it may be too fluffy like a chocolate cake; or it may be too heavy like a dense fudge). We therefore love the chocolate brownie because it has several delightful, distinguishing, and delicious features. Selecting good features in our data collection similarly delights us in many ways.

MCLEAN, Va.--(BUSINESS WIRE)--Over the last four years, more than 50,000 participants have developed and submitted over 114,000 artificial intelligence (AI) algorithms to improve everything from detection of lung cancer and heart disease, to monitoring ocean health and helping accelerate life-saving medical research as part of the annual Data Science Bowl . In partnership with PBS KIDS, this year's competition will look at advancements in early childhood education. The results will lead to better designed games and improved learning outcomes, empowering children, parents, caregivers and educators across the globe with insights into how young children learn through media and which approaches work best to help them build on foundational learning skills. The 90-day Data Science Bowl competition will award winning participants with a share of $160,000 in cash prizes. Research shows much of the most critical brain development in children takes place before they even reach kindergarten.

In partnership with PBS KIDS, this year's competition will look at advancements in early childhood education. The results will lead to better designed games and improved learning outcomes, empowering children, parents, caregivers, and educators across the globe with insights into how young children learn through media and which approaches work best to help them build on foundational learning skills. The 90-day Data Science Bowl competition will award winning participants with a share of $160,000 in cash prizes. Research shows much of the most critical brain development in children takes place before they even reach kindergarten. Child development experts indicate it is during these first 5 years that children develop linguistic, cognitive, social, emotional, and regulatory skills that predict their later functioning in many domains.

Over the last four years, more than 50,000 participants have developed and submitted over 114,000 artificial intelligence (AI) algorithms to improve everything from detection of lung cancer and heart disease, to monitoring ocean health and helping accelerate life-saving medical research as part of the annual Data Science Bowl . In partnership with PBS KIDS, this year's competition will look at advancements in early childhood education. The results will lead to better designed games and improved learning outcomes, empowering children, parents, caregivers and educators across the globe with insights into how young children learn through media and which approaches work best to help them build on foundational learning skills. The 90-day Data Science Bowl competition will award winning participants with a share of $160,000 in cash prizes. Research shows much of the most critical brain development in children takes place before they even reach kindergarten.

The Bonnie J. Addario Lung Cancer Foundation recently brought together more than 650 data scientists, engineers and designers from 68 countries to build open source tools to fight the world's deadliest cancer. During the Concept to Clinic Challenge, contributors built state-of-the-art algorithms applied to the detection and assessment of lung nodules from CT scans to bring advancements in machine learning into medical clinics. The foundation put up $100,000 in prizes for top contributors. Willi Gierke, a student who is getting his masters in IT/systems engineering at Hasso Plattner Institute in Potsdam, Germany, was the top prizewinner, taking home more than $30,000. The code developed during this challenge is openly available for anyone to learn from and use.

Three, it turns out, is better than one. At least that's how it worked for a trio of former rivals who teamed up to claim the just-announced top prize in this year's Data Science Bowl. The fourth annual event focused on one of healthcare's most pressing problems -- the soaring cost and time needed to discover new drugs. A record-setting 18,000 participants battled over 90 days to deliver a deep learning algorithm to accelerate a crucial step in the drug-discovery pipeline: identifying the nucleus of each cell. This year's Data Science Bowl was "driven by a very real need to develop new treatments faster and more accurately," said Anne Carpenter, director of the imaging platform at the Broad Institute of MIT and Harvard, the nonprofit partner for the contest.

Imagine unleashing the power of artificial intelligence to automate a critical component of biomedical research, expediting life-saving research in the treatment of almost every disease from rare disorders to the common cold. This could soon be a reality, thanks to the fourth Data Science Bowl, a 90-day competition in which, for the very first time, participants trained deep learning models to examine images of cells and identify nuclei, regardless of the experimental setup--and without human intervention. Algorithms developed in this competition could save researchers hundreds of thousands of hours of effort per year. This year, the competition brought together nearly 18,000 global participants, the most ever for the Data Science Bowl. Collectively, they submitted more than 68,000 algorithms and worked an estimated 288,000 hours to automate the vital, but time-consuming, process of nuclei detection.

After 90 days and 288,000 working hours, the much-discussed fourth annual Data Science Bowl has ended. Run by Booz Allen Hamilton and Kaggle, the contest resulted in 68,000 algorithms, 3 winners, and one tantalizing opportunity for biomedical research. The goal of this year's Data Science Bowl was to build artificial intelligence (AI) systems that could automate what organizers called a "critical component of biomedical research." As such, 18,000 competitors spent months honing deep-learning models to scrutinize images of cells in search of nuclei, all without aid from humans. The ensuing algorithms are expected to salvage hundreds of thousands of hours each year, time that was previously burned by researchers who were forced to perform the task, according to the organizers.