Booz Allen Hamilton and data science community website Kaggle have launched the fourth annual Data Science Bowl, challenging participants to develop algorithms capable of automating nucleus detection in medical imagery. Identifying cell nuclei in samples allows researchers to identify individual cells and monitor how they react to different treatments, which is a key step in developing and testing new drugs. Bringing a new drug to market typically takes 10 years, and automating nucleus detection would accelerate this process. Participants have access to training datasets of nuclei imagery from a variety of cell types taken in different conditions. Participants have 90 days to develop their algorithms and winning teams could receive up to $170,000.
Detecting Nuclei for the Super Bowl of Data Science
Joshua New was a senior policy analyst at the Center for Data Innovation. He has a background in government affairs, policy, and communication. Prior to joining the Center for Data Innovation, Joshua graduated from American University with degrees in C.L.E.G. (Communication, Legal Institutions, Economics, and Government) and Public Communication. His research focuses on methods of promoting innovative and emerging technologies as a means of improving the economy and quality of life.
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