Asgari M - Search Results

1

Predicting mild cognitive impairment from spontaneous spoken utterances.

Asgari M, Kaye J, Dodge H. Asgari M, et al. Alzheimers Dement (N Y). 2017 Feb 27;3(2):219-228. doi: 10.1016/j.trci.2017.01.006. eCollection 2017 Jun. Alzheimers Dement (N Y). 2017. PMID: 29067328 Free PMC article.

2

Social Markers of Mild Cognitive Impairment: Proportion of Word Counts in Free Conversational Speech.

Dodge HH, Mattek N, Gregor M, Bowman M, Seelye A, Ybarra O, Asgari M, Kaye JA. Dodge HH, et al. Among authors: asgari m. Curr Alzheimer Res. 2015;12(6):513-9. doi: 10.2174/1567205012666150530201917. Curr Alzheimer Res. 2015. PMID: 26027814 Free PMC article. Clinical Trial.

3

Improving the Assessment of Mild Cognitive Impairment in Advanced Age With a Novel Multi-Feature Automated Speech and Language Analysis of Verbal Fluency.

Chen L, Asgari M, Gale R, Wild K, Dodge H, Kaye J. Chen L, et al. Among authors: asgari m. Front Psychol. 2020 Apr 9;11:535. doi: 10.3389/fpsyg.2020.00535. eCollection 2020. Front Psychol. 2020. PMID: 32328008 Free PMC article.

4

Automatic Assessment of Cognitive Tests for Differentiating Mild Cognitive Impairment: A Proof of Concept Study of the Digit Span Task.

Asgari M, Gale R, Wild K, Dodge H, Kaye J. Asgari M, et al. Curr Alzheimer Res. 2020;17(7):658-666. doi: 10.2174/1567205017666201008110854. Curr Alzheimer Res. 2020. PMID: 33032509 Free PMC article.

5

INFERRING CLINICAL DEPRESSION FROM SPEECH AND SPOKEN UTTERANCES.

Asgari M, Shafran I, Sheeber LB. Asgari M, et al. IEEE Int Workshop Mach Learn Signal Process. 2014 Sep;2014:10.1109/mlsp.2014.6958856. doi: 10.1109/mlsp.2014.6958856. Epub 2014 Nov 20. IEEE Int Workshop Mach Learn Signal Process. 2014. PMID: 33288990 Free PMC article.

6

Topic-Based Measures of Conversation for Detecting Mild Cognitive Impairment.

Chen L, Dodge HH, Asgari M. Chen L, et al. Among authors: asgari m. Proc Conf Assoc Comput Linguist Meet. 2020 Jul;2020:63-67. Proc Conf Assoc Comput Linguist Meet. 2020. PMID: 33642674 Free PMC article.

7

OPTIMIZE WAV2VEC2S ARCHITECTURE FOR SMALL TRAINING SET THROUGH ANALYZING ITS PRE-TRAINED MODELS ATTENTION PATTERN.

Chen L, Asgari M, Dodge HH. Chen L, et al. Among authors: asgari m. Proc IEEE Int Conf Acoust Speech Signal Process. 2022 May;2022:7112-7116. doi: 10.1109/icassp43922.2022.9747831. Epub 2022 Apr 27. Proc IEEE Int Conf Acoust Speech Signal Process. 2022. PMID: 37193061 Free PMC article.

8

Fully Automated Assessment of the Severity of Parkinson's Disease from Speech.

Bayestehtashk A, Asgari M, Shafran I, McNames J. Bayestehtashk A, et al. Among authors: asgari m. Comput Speech Lang. 2015 Jan;29(1):172-185. doi: 10.1016/j.csl.2013.12.001. Comput Speech Lang. 2015. PMID: 25382935 Free PMC article.

9

AUTOMATIC MEASUREMENT OF AFFECTIVE VALENCE AND AROUSAL IN SPEECH.

Asgari M, Kiss G, van Santen J, Shafran I, Song X. Asgari M, et al. Proc IEEE Int Conf Acoust Speech Signal Process. 2014 May;2014:965-969. doi: 10.1109/ICASSP.2014.6853740. Epub 2014 Jul 14. Proc IEEE Int Conf Acoust Speech Signal Process. 2014. PMID: 33642942 Free PMC article.

10

Predicting severity of Parkinson's disease from speech.

Asgari M, Shafran I. Asgari M, et al. Annu Int Conf IEEE Eng Med Biol Soc. 2010;2010:5201-4. doi: 10.1109/IEMBS.2010.5626104. Annu Int Conf IEEE Eng Med Biol Soc. 2010. PMID: 21095825 Free PMC article.

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