Grants We Funded
Grant applicants for the 2023 cycle requested a total of nearly $4 million dollars. The PSF Study Section Subcommittees of Basic & Translational Research and Clinical Research evaluated nearly 140 grant applications on the following topics:
The PSF awarded research grants totaling over $1 million dollars to support nearly 30 plastic surgery research proposals.
ASPS/PSF leadership is committed to continuing to provide high levels of investigator-initiated research support to ensure that plastic surgeons have the needed research resources to be pioneers and innovators in advancing the practice of medicine.
Research Abstracts
Search The PSF database to have easy access to full-text grant abstracts from past PSF-funded research projects 2003 to present. All abstracts are the work of the Principal Investigators and were retrieved from their PSF grant applications. Several different filters may be applied to locate abstracts specific to a particular focus area or PSF funding mechanism.
Transforming Cleft Speech Assessment and Care through Online Crowdsourcing
Principal Investigator
Alexander Lin MD
Alexander Lin MD
Year
2020
2020
Institution
Saint Louis University
Saint Louis University
Funding Mechanism
Translational and Innovation Research Grant
Translational and Innovation Research Grant
Focus Area
Cranio/Maxillofacial/Head and Neck, Technology Based
Cranio/Maxillofacial/Head and Neck, Technology Based
Abstract
Project Summary: Speech is essential for social development. For children born with cleft palate, this speech is compromised. The goal of cleft palate repair is to repair the palate and restore normal human speech. However, “normal speech” is a subjective quality, making it difficult to assess. Although speech language pathology (SLP) evaluation is the gold-standard, there is a shortage of speech experts making this assessment costly and not easily accessible to all children with cleft palate. Online crowdsourcing is a burgeoning technology may offer an alternative form of speech assessment. Amazon Mechanical Turk (MTurk) is a crowdsourcing platform that has lay people perform tasks for nominal fees, and is capable of rapidly generating large volume of data. This project will be the first of its kind to employ this novel crowdsourcing technology to help children with cleft palate. Preliminary data from our center suggests that MTurk-generated ratings of audio clips of cleft speech are highly concordant with expert SLP evaluation. With this knowledge, we intend to show that MTurk is an accurate model that can be used in research and clinical settings as both a proxy and adjunct to SLP ratings. In addition, we have piloted a mobile phone application (app) capable of recording high-quality speech in non-clinical settings. We intend to use this app as a platform that can interface with SLPs and MTurk to generate perceptual speech ratings. Finally, we will marry crowdsourcing to yet another new technology- machine learning. Machine learning (ML) computer programs are designed to improve with experience. We will use a Markov Decision Process, where outcomes are determined partially by a decision maker (the SLP overseeing the algorithim's use) and partially based on probability calculations from large scale data analysis (perceptual speech ratings generated from SLPs and MTurk). The result will be a program that can analyze a child's speech and generate treatment patient-specific suggestions based on the child's changing speech patterns. This can complement SLP evaluations and screen children for treatment, especially in remote or rural areas with limited access to speech experts. Impact Statement: Online crowdsourcing of perceptual speech will generate a powerful tool for researchers and clinicians to assess speech as an alternative to speech expert evaluations which are limited by cost and access. Our new mobile app will capture high-quality sound volume and be able to interface with speech experts or MTurk, making speech ratings even easier. Finally, machine learning will be used as an adjunct to provide personalized medicine to children with cleft palate to help improve their speech and overall care.
Project Summary: Speech is essential for social development. For children born with cleft palate, this speech is compromised. The goal of cleft palate repair is to repair the palate and restore normal human speech. However, “normal speech” is a subjective quality, making it difficult to assess. Although speech language pathology (SLP) evaluation is the gold-standard, there is a shortage of speech experts making this assessment costly and not easily accessible to all children with cleft palate. Online crowdsourcing is a burgeoning technology may offer an alternative form of speech assessment. Amazon Mechanical Turk (MTurk) is a crowdsourcing platform that has lay people perform tasks for nominal fees, and is capable of rapidly generating large volume of data. This project will be the first of its kind to employ this novel crowdsourcing technology to help children with cleft palate. Preliminary data from our center suggests that MTurk-generated ratings of audio clips of cleft speech are highly concordant with expert SLP evaluation. With this knowledge, we intend to show that MTurk is an accurate model that can be used in research and clinical settings as both a proxy and adjunct to SLP ratings. In addition, we have piloted a mobile phone application (app) capable of recording high-quality speech in non-clinical settings. We intend to use this app as a platform that can interface with SLPs and MTurk to generate perceptual speech ratings. Finally, we will marry crowdsourcing to yet another new technology- machine learning. Machine learning (ML) computer programs are designed to improve with experience. We will use a Markov Decision Process, where outcomes are determined partially by a decision maker (the SLP overseeing the algorithim's use) and partially based on probability calculations from large scale data analysis (perceptual speech ratings generated from SLPs and MTurk). The result will be a program that can analyze a child's speech and generate treatment patient-specific suggestions based on the child's changing speech patterns. This can complement SLP evaluations and screen children for treatment, especially in remote or rural areas with limited access to speech experts. Impact Statement: Online crowdsourcing of perceptual speech will generate a powerful tool for researchers and clinicians to assess speech as an alternative to speech expert evaluations which are limited by cost and access. Our new mobile app will capture high-quality sound volume and be able to interface with speech experts or MTurk, making speech ratings even easier. Finally, machine learning will be used as an adjunct to provide personalized medicine to children with cleft palate to help improve their speech and overall care.
Biography
Dr. Alexander Y. Lin was raised in New York City, and graduated from Stanford University with a bachelor’s in Psychology, and a master’s in Statistics. He received his M.D. from Johns Hopkins School of Medicine. He then completed surgical residency in General Surgery and Plastic and Reconstructive Surgery at University of California San Francisco (UCSF), including a two-year research fellowship at Massachusetts General Hospital in vascular immunobiology. He completed his fellowship in Craniofacial and Pediatric Plastic Surgery at Children’s Hospital of Pittsburgh (CHP) of University of Pittsburgh Medical Center (UPMC). At Saint Louis University (SLU), he is the Alan A. and Edith L. Wolff Endowed Chair in Craniofacial, Maxillofacial, and Pediatric Plastic Surgery, Associate Professor of Surgery and Orthodontics, and a board member on the Board of Advisors for SLU MEDLaunch, their medical incubator for innovation.
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Pediatric Plastic Surgery treats the things that make us uniquely human: our faces, our speech (from our palate), and our ability to use our hands. Without these normal human functions, children cannot interact with others and develop normally. His goal is to give these children the opportunity to live as normal a life as possible. He is the co-founder and surgical director for the 3D Printing Center of Excellence at Cardinal Glennon. His surgery, research, and inventions, focus on improving the lives of children and their families.
Dr. Alexander Y. Lin was raised in New York City, and graduated from Stanford University with a bachelor’s in Psychology, and a master’s in Statistics. He received his M.D. from Johns Hopkins School of Medicine. He then completed surgical residency in General Surgery and Plastic and Reconstructive Surgery at University of California San Francisco (UCSF), including a two-year research fellowship at Massachusetts General Hospital in vascular immunobiology. He completed his fellowship in Craniofacial and Pediatric Plastic Surgery at Children’s Hospital of Pittsburgh (CHP) of University of Pittsburgh Medical Center (UPMC). At Saint Louis University (SLU), he is the Alan A. and Edith L. Wolff Endowed Chair in Craniofacial, Maxillofacial, and Pediatric Plastic Surgery, Associate Professor of Surgery and Orthodontics, and a board member on the Board of Advisors for SLU MEDLaunch, their medical incubator for innovation.
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Pediatric Plastic Surgery treats the things that make us uniquely human: our faces, our speech (from our palate), and our ability to use our hands. Without these normal human functions, children cannot interact with others and develop normally. His goal is to give these children the opportunity to live as normal a life as possible. He is the co-founder and surgical director for the 3D Printing Center of Excellence at Cardinal Glennon. His surgery, research, and inventions, focus on improving the lives of children and their families.