Matching Items (802)
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- Creators: Novak, Gail (Pianist)
ContributorsKierum, Caitlin (Contributor) / Novak, Gail (Pianist) (Performer) / Liang, Jack (Performer) / ASU Library. Music Library (Publisher)
Created2018-04-11
ContributorsLougheed, Julia (Performer) / Novak, Gail (Pianist) (Performer) / Bayer, Elizabeth Kennedy (Performer) / Clifton-Armenta, Tyler (Performer) / Park, Julie (Performer) / Javier de Alba, Francisco (Performer) / Vientos Dulces (Performer) / ASU Library. Music Library (Publisher)
Created2018-04-07
ContributorsCoffey, Brennan (Performer) / Novak, Gail (Pianist) (Performer) / ASU Library. Music Library (Publisher)
Created2021-04-26
ContributorsHolly, Sean (Performer) / Wright, Aaron (Performer) / Novak, Gail (Pianist) (Performer) / ASU Library. Music Library (Publisher)
Created2021-04-29
ContributorsBreeden, Katherine (Performer) / German, Lindsey (Performer) / Novak, Gail (Pianist) (Performer) / ASU Library. Music Library (Publisher)
Created2018-04-13
Description
ABSTRACT Many musicians, both amateur and professional alike, are continuously seeking to expand and explore their performance literature and repertory. Introducing new works into the standard repertory is an exciting endeavor for any active musician. Establishing connections, commissioning new works, and collaborating on performances can all work together toward the acceptance and success of a composer's music within an instrument community. For the flute, one such composer is Daniel Dorff (b. 1956). Dorff, a Philadelphia-based composer, has written for symphony orchestra, clarinet, contrabassoon, and others; however, his award-winning works for flute and piccolo are earning him much recognition. He has written works for such illustrious flutists as Mimi Stillman, Walfrid Kujala, and Gary Schocker; his flute works have been recorded by Laurel Zucker, Pamela Youngblood and Lois Bliss Herbine; and his pieces have been performed and premiered at each of the National Flute Association Conventions from 2004 to 2009. Despite this success, little has been written about Dorff's life, compositional style, and contributions to the flute repertory. In order to further promote the flute works of Daniel Dorff, the primary focus of this study is the creation of a compact disc recording of Dorff's most prominent works for flute: April Whirlwind, 9 Walks Down 7th Avenue, both for flute and piano, and Nocturne Caprice for solo flute. In support of this recording, the study also provides biographical information regarding Daniel Dorff, discusses his compositional methods and ideology, and presents background information, description, and performance notes for each piece. Interviews with Daniel Dorff regarding biographical and compositional details serve as the primary source for this document. Suggestions for the performance of the three flute works were gathered through interviews with prominent flutists who have studied and performed Dorff's pieces. Additional performance suggestions for Nocturne Caprice were gathered through a coaching session between the author and the composer. This project is meant to promote the flute works of Daniel Dorff and to help establish their role in the standard flute repertory.
ContributorsRich, Angela Marie (Contributor) / Novak, Gail (Pianist) (Performer) / Buck, Elizabeth Y (Thesis advisor) / Hill, Gary W. (Committee member) / Holbrook, Amy (Committee member) / Schuring, Martin (Committee member) / Arizona State University (Publisher)
Created2010
ContributorsBroome-Robinson, Julia (Performer) / Novak, Gail (Pianist) (Performer) / Glick, Philip (Performer) / Lynch, Paul (Performer) / Ryall, Blake (Performer) / ASU Library. Music Library (Publisher)
Created2018-10-19
Description
Background: Pulmonary embolism is a deadly condition that is often diagnosed using a technique known as computed tomography pulmonary angiography (CTPA). CTPA reports are free-text, narrative-style forms of documentation conferring radiologist findings—both primary (regarding pulmonary embolism) and incidental. This project seeks to combine simple natural language processing (NLP) techniques, such as regular expressions and rules, to build upon and
further process output from a machine learning based named entity recognition (NER) tool for the purposes of (1) linking references to radiological images with the corresponding clinical findings and (2) extracting primary and incidental findings.
Methods: The project’s system utilized a regular expression to extract image references. All CTPA reports were first processed with NER software to obtain the text and spans of clinical findings. A heuristic was used to determine the appropriate clinical finding that should be linked with a particular image reference. Another regular expression was used to extract primary findings from NER output; the remaining findings were considered incidental. Performance was
assessed against a gold standard, which was based upon a manually annotated version of the CTPA reports used in this project.
Results: Extraction of image references achieved a 100% accuracy. Linkages between these references and exact gold standard spans of the clinical findings achieved a precision of 0.24, a recall of 0.22, and an F1 score of 0.23. Linkages with partial spans of clinical findings as determined by the gold standard achieved a precision of 0.71, a recall of 0.67, and an F1 score of 0.69. Primary and incidental finding extraction achieved a precision of 0.67, a recall of 0.80, and
an F1 score of 0.73.
Discussion: Various elements reduced system performance such as the difficulty of exactly matching the spans of clinical findings from NER output with those found in the gold standard. The heuristic linking clinical findings and image references was especially sensitive to NER false positives and false negatives due to its assumption that the appropriate clinical finding was that which was immediately prior to the image reference. Although the system did not perform as well as hoped, lessons were learned such as the need for clear research methodology and proper gold standard creation; without a proper gold standard, problem scope and system performance cannot be properly assessed. Improvements to the system include creating a more robust heuristic, sifting NER false positives, and training the NER tool used on a dataset of CTPA reports.
further process output from a machine learning based named entity recognition (NER) tool for the purposes of (1) linking references to radiological images with the corresponding clinical findings and (2) extracting primary and incidental findings.
Methods: The project’s system utilized a regular expression to extract image references. All CTPA reports were first processed with NER software to obtain the text and spans of clinical findings. A heuristic was used to determine the appropriate clinical finding that should be linked with a particular image reference. Another regular expression was used to extract primary findings from NER output; the remaining findings were considered incidental. Performance was
assessed against a gold standard, which was based upon a manually annotated version of the CTPA reports used in this project.
Results: Extraction of image references achieved a 100% accuracy. Linkages between these references and exact gold standard spans of the clinical findings achieved a precision of 0.24, a recall of 0.22, and an F1 score of 0.23. Linkages with partial spans of clinical findings as determined by the gold standard achieved a precision of 0.71, a recall of 0.67, and an F1 score of 0.69. Primary and incidental finding extraction achieved a precision of 0.67, a recall of 0.80, and
an F1 score of 0.73.
Discussion: Various elements reduced system performance such as the difficulty of exactly matching the spans of clinical findings from NER output with those found in the gold standard. The heuristic linking clinical findings and image references was especially sensitive to NER false positives and false negatives due to its assumption that the appropriate clinical finding was that which was immediately prior to the image reference. Although the system did not perform as well as hoped, lessons were learned such as the need for clear research methodology and proper gold standard creation; without a proper gold standard, problem scope and system performance cannot be properly assessed. Improvements to the system include creating a more robust heuristic, sifting NER false positives, and training the NER tool used on a dataset of CTPA reports.
ContributorsBorlongan, Matthew Bilog (Author) / Devarakonda, Murthy (Thesis director) / Murcko, Anita (Committee member) / College of Health Solutions (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
ContributorsCrimminger, Jordan (Performer) / Novak, Gail (Pianist) (Performer) / Hong, Dylan (Performer) / Larson, Ben (Performer) / Russell, Liam (Performer) / Raschko, Hannah (Performer) / ASU Library. Music Library (Publisher)
Created2017-10-22
ContributorsStrickland, Kiefer (Performer) / Novak, Gail (Pianist) (Performer) / McKinch, Riley (Performer) / Hoeckley, Stephanie (Performer) / Bates-Kennard, Sarah (Performer) / Moonitz, Olivia (Performer) / Lovelady, Alexis (Performer) / ASU Library. Music Library (Publisher)
Created2017-10-31