New York Methodist Hospital Park Slope Infusion Center 343 4 Ave, Brooklyn, NY 11215 (718)4992169 (phone), (718)4993218 (fax)
New York Methodist Hospital Hematology Oncology 501 6 St APT 3C, Brooklyn, NY 11215 (718)7805541 (phone), (718)7805545 (fax)
Education:
Medical School University of Iowa Carver College of Medicine Graduated: 1977
Procedures:
Bone Marrow Biopsy Bone Marrow or Stem Cell Transplant
Conditions:
Sickle-Cell Disease Anemia Hemolytic Anemia Hodgkin's Lymphoma Iron Deficiency Anemia
Languages:
English Spanish
Description:
Dr. Cook graduated from the University of Iowa Carver College of Medicine in 1977. He works in Brooklyn, NY and 1 other location and specializes in Hematology/Oncology. Dr. Cook is affiliated with New York Methodist Hospital.
Wind River Radiology PC 1320 Bishop Randall Dr, Lander, WY 82520 (307)3356451 (phone), (307)3324276 (fax)
Education:
Medical School Duke University School of Medicine Graduated: 1988
Languages:
English
Description:
Dr. Cook graduated from the Duke University School of Medicine in 1988. She works in Lander, WY and specializes in Diagnostic Radiology and Radiology. Dr. Cook is affiliated with SageWest Health Care Lander.
Wikipedia References
Perry R. Cook
Us Patents
Self Organizing Maps (Soms) For Organizing, Categorizing, Browsing And/Or Grading Large Collections Of Assignments For Massive Online Education Systems
- Valencia CA, US Ajay Kapur - Valencia CA, US Owen S. Vallis - Valencia CA, US Perry R. Cook - Jacksonville OR, US Colin Honigman - Valencia CA, US Chad Wagner - Pasadena CA, US
International Classification:
G09B 19/00 G06F 17/30 G09B 5/06
US Classification:
434118, 434350, 707738
Abstract:
For courses that deal with media content, such as sound, music, photographic images, hand sketches, video, conventional techniques for automatically evaluating and grading assignments are generally ill-suited to direct evaluation of coursework submitted in media-rich form. Likewise, for courses whose subject includes programming, signal processing or other functionally-expressed designs that operate on, or are used to produce media content, conventional techniques are also ill-suited. Instead, it has been discovered that media-rich, indeed even expressive, content can be accommodated as, or as derivatives of, submissions using feature extraction and machine learning techniques. In this way, e.g., in on-line course offerings, even large numbers of students and student submissions may be accommodated in a scalable and uniform grading or scoring scheme. Likewise, large collections of coursework submissions (whether or not graded or scored) or media content more generally, may be efficiently browsed and grouped using techniques described herein.
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