Jochen Weiner, C. Frankenberg, J. Schröder, Tanja Schultz
{"title":"言语揭示未来患痴呆症的风险:从传记访谈中预测痴呆症筛查","authors":"Jochen Weiner, C. Frankenberg, J. Schröder, Tanja Schultz","doi":"10.1109/ASRU46091.2019.9003908","DOIUrl":null,"url":null,"abstract":"Alzheimer's disease is a progressive incurable condition for which the success of any symptomatic therapy depends crucially on the starting time. Ideally it starts before the disease has caused any cognitive impairments. Our work aims at developing speech-based dementia screening methods that detect dementia as early as possible. Here, we aim to predict the outbreak even before clinical screening tests can diagnose the disease. Using the longitudinal ILSE study, we automatically extract features from biographic interviews and predict the development of dementia 5 and 12 years into the future. Our prediction system achieves results of 73.3% and 75.7% unweighted average recall (UAR), respectively, which clearly outperform a prediction based on prior diagnoses or disease prevalence. Thus, the automated analysis of spoken interviews offers a highly effective prediction procedure that allows for easy-to-use, cost-effective casual testing.","PeriodicalId":150913,"journal":{"name":"2019 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"Speech Reveals Future Risk of Developing Dementia: Predictive Dementia Screening from Biographic Interviews\",\"authors\":\"Jochen Weiner, C. Frankenberg, J. Schröder, Tanja Schultz\",\"doi\":\"10.1109/ASRU46091.2019.9003908\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Alzheimer's disease is a progressive incurable condition for which the success of any symptomatic therapy depends crucially on the starting time. Ideally it starts before the disease has caused any cognitive impairments. Our work aims at developing speech-based dementia screening methods that detect dementia as early as possible. Here, we aim to predict the outbreak even before clinical screening tests can diagnose the disease. Using the longitudinal ILSE study, we automatically extract features from biographic interviews and predict the development of dementia 5 and 12 years into the future. Our prediction system achieves results of 73.3% and 75.7% unweighted average recall (UAR), respectively, which clearly outperform a prediction based on prior diagnoses or disease prevalence. Thus, the automated analysis of spoken interviews offers a highly effective prediction procedure that allows for easy-to-use, cost-effective casual testing.\",\"PeriodicalId\":150913,\"journal\":{\"name\":\"2019 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ASRU46091.2019.9003908\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ASRU46091.2019.9003908","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Speech Reveals Future Risk of Developing Dementia: Predictive Dementia Screening from Biographic Interviews
Alzheimer's disease is a progressive incurable condition for which the success of any symptomatic therapy depends crucially on the starting time. Ideally it starts before the disease has caused any cognitive impairments. Our work aims at developing speech-based dementia screening methods that detect dementia as early as possible. Here, we aim to predict the outbreak even before clinical screening tests can diagnose the disease. Using the longitudinal ILSE study, we automatically extract features from biographic interviews and predict the development of dementia 5 and 12 years into the future. Our prediction system achieves results of 73.3% and 75.7% unweighted average recall (UAR), respectively, which clearly outperform a prediction based on prior diagnoses or disease prevalence. Thus, the automated analysis of spoken interviews offers a highly effective prediction procedure that allows for easy-to-use, cost-effective casual testing.