PROJECT SUMMARY/ABSTRACT The over-arching goals of Dr, Rameau's Beeson application are (1) to develop an easy-to-use, highly accurate bedside clinical decision support tool to identify swallowing dysfunction in older adults using analysis of features of their recorded voice, cough and speech, and (2) to become a leader in the nascent field of geriatric otolaryngology with a focus on management of speech and swallowing issues in older adults with Alzheimer's disease and related dementias (AD/ADRD). Candidate: The applicant, Dr. Anaïs Rameau, is an otolaryngologist at Weill Cornell Medical College (WCMC) who has demonstrated significant research ability and clinical interest in geriatric otolaryngology, especially in the care of older adults with dysphagia. Dr. Rameau's long-term career goal is to become an independent researcher and academic leader in geriatric dysphagia. She already laid significant foundations towards this goal, developing close mentorship relationships, gaining broad research, clinical, management and leadership skills, and experience as PI on multiple institutional and foundation grants. Mentors: To achieve her objectives, Dr. Rameau has engaged an exceptional, transdisciplinary team of mentors, who are highly successful, NIH-funded investigators and well-recognized leaders and experts in their respective fields. Her mentorship team includes Dr. Mark Lachs, Co-Director of the WCMC Division of Geriatrics, Dr. Michael Stewart, Chair of the WCM Department of Otolaryngology – Head & Neck Surgery, and Dr. Sara Czaja, Director of the Center on Aging and Behavioral Research at WCM. Research: In collaboration with bio-acousticians at the Cornell Lab of Ornithology, our research, both in an excised canine model and a human pilot study, has suggested that conventional acoustic metrics of voice and cough sound differ in important ways between patients with and without aspiration risk. These characteristics may serve as biomarkers of dysphagia, and acoustic analysis of the patient's digitally recorded voice and cough has the potential to effectively differentiate between normal and abnormal swallowing. Including multiple characteristics, such as those specifically evaluating oral frailty, and combining the results may increase accuracy of swallowing dysfunction identification, especially in older adults with AD/ADRD who are more prone to silent aspiration. Adding non-linear methods and machine learning to conventional acoustic analysis may also improve accuracy. Dr. Rameau proposes to use these techniques to develop a clinical decision support tool that incorporates analysis of multiple characteristics of a patient's recorded voice and cough to determine their aspiration risk. To increase the potential for use of this tool at the bedside, she will modify it for recordings on a smartphone as part of a mobile application. Upon completion of this research, she plans to submit an R01 to prospectively examine the performance of the clinical de...