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Effectiveness of Voice Quality Features in Detecting Depression.

, , , , , and . INTERSPEECH, page 1676-1680. ISCA, (2018)

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A Step Towards Preserving Speakers' Identity While Detecting Depression Via Speaker Disentanglement., , , and . INTERSPEECH, page 3338-3342. ISCA, (2022)Personalized mood prediction from patterns of behavior collected with smartphones., , , , , , , , , and 8 other author(s). npj Digit. Medicine, (2024)Management, presentation and interpretation of genome scans using GSCANDB., , , , and . Bioinform., 23 (12): 1545-1549 (2007)Leveraging eQTLs to identify individual-level tissue of interest for a complex trait., , , , , , , and . PLoS Comput. Biol., (2021)Identifying comorbidities from depressed people via voice analysis., , , and . BIBM, page 986-991. IEEE Computer Society, (2017)Effectiveness of Voice Quality Features in Detecting Depression., , , , , and . INTERSPEECH, page 1676-1680. ISCA, (2018)Automatic analysis of agarose gel images., , , , , , , and . Bioinform., 17 (11): 1084-1089 (2001)Power failure: why small sample size undermines the reliability of neuroscience., , , , , , and . Nature reviews. Neuroscience, 14 (5): 365-76 (May 2013)Significació estadística; Estudi petit; Bias; Errors.An efficient tool for genetic experiments: agarose gel image analysis., and . Pattern Recognit., 36 (10): 2453-2461 (2003)Detecting Postpartum Depression in Depressed People by Speech Features., , , , , , , and . HCC, volume 10745 of Lecture Notes in Computer Science, page 433-442. Springer, (2017)