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Knowledge Discovery and Data Mining focuses on the process of extracting meaningful patterns from biomedical data (knowledge discovery), using automated computational and statistical tools and techniques on large datasets (data mining).

Its underlying goal is to help humans make high-level sense of large volumes of low-level data, and share that knowledge with colleagues in related fields. It can involve methods for data preparation, cleaning, and selection, use of appropriate prior knowledge, development and application of data mining algorithms, and proper results analysis.

It engages methods from such diverse areas as machine learning, pattern recognition, database science, statistics and analytics, artificial intelligence, knowledge acquisition for expert systems, data modeling and visualization, and high performance computing.

 

Leadership

Profile image for Zhe He, PhD, FIAHSI, FAMIA

Zhe He, PhD, FIAHSI, FAMIA

Chair
Professor & Informatics Lead
Florida State University
Profile image for Hilda Klasky, FAMIA

Hilda Klasky, FAMIA

Vice Chair
Senior R&D Staff
Oak Ridge National Laboratory (ORNL) - UT Battelle
Profile image for Jakir Hossain Bhuiyan Masud, PhD

Jakir Hossain Bhuiyan Masud, PhD

Vice Chair
Dr.
University of Alabama at Birmingham
Profile image for Carl Yang, Ph.D.

Carl Yang, Ph.D.

Chair Elect
Associate Professor
Emory University
Profile image for Humayera Islam, MSc, MSHI, PhD

Humayera Islam, MSc, MSHI, PhD

Secretary
Postdoctoral Scholar
The University of Chicago
Profile image for Navya Martin Kollapally, PhD in Computer Science

Navya Martin Kollapally, PhD in Computer Science

Member-at-Large
Assistant Professor
Kean University

 


  • Performing: Working Group has high level of engagement and output (workshops, papers, webinars)
  • Networking: Working Group has internal and external networking opportunities for members (mentorship programs, social events, collaboration)
  • Developing: New Working Group or revitalizing efforts to grow membership (recruitment efforts, leadership)
Phenotypes
Performing: 60%
Networking: 20%
Developing: 20%

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