Guess What We Can Hear – Novel Voice Biomarkers for the Remote Detection of Disease
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[1] D. Orbelo,et al. Noninvasive Voice Biomarker Is Associated With Incident Coronary Artery Disease Events at Follow-up. , 2022, Mayo Clinic proceedings.
[2] A. Lerman,et al. The endothelium is a key player in the vascular response to acute mental stress. , 2021, European heart journal.
[3] A. Guidi,et al. Vocal features obtained through automated methods in verbal fluency tasks can aid the identification of mixed episodes in bipolar disorder , 2021, Translational Psychiatry.
[4] E. Zimlichman,et al. Noninvasive Vocal Biomarker is Associated With Severe Acute Respiratory Syndrome Coronavirus 2 Infection , 2021, Mayo Clinic Proceedings: Innovations, Quality & Outcomes.
[5] Kyogu Lee,et al. Screening major depressive disorder using vocal acoustic features in the elderly by sex. , 2021, Journal of affective disorders.
[6] G. Fagherazzi,et al. Voice for Health: The Use of Vocal Biomarkers from Research to Clinical Practice , 2021, Digital Biomarkers.
[7] Allison J. Ober,et al. Telehealth Use Among Safety-Net Organizations in California During the COVID-19 Pandemic. , 2021, JAMA.
[8] Adil Alaoui,et al. Acoustic and language analysis of speech for suicidal ideation among US veterans , 2021, BioData Mining.
[9] Ravi Vaidyanathan,et al. Telemonitoring Parkinson’s disease using machine learning by combining tremor and voice analysis , 2020, Brain Informatics.
[10] Brian Subirana,et al. COVID-19 Artificial Intelligence Diagnosis Using Only Cough Recordings , 2020, IEEE Open Journal of Engineering in Medicine and Biology.
[11] M. Mimura,et al. Using speech recognition technology to investigate the association between timing-related speech features and depression severity , 2020, PloS one.
[12] W. Hooten,et al. The Effects of COVID-19 on Telemedicine Could Outlive the Virus , 2020, Mayo Clinic Proceedings: Innovations, Quality & Outcomes.
[13] Larry Zhang,et al. Automated voice biomarkers for depression symptoms using an online cross‐sectional data collection initiative , 2020, Depression and anxiety.
[14] Amir Lerman,et al. Non-invasive vocal biomarker is associated with pulmonary hypertension , 2020, PloS one.
[15] Ariel V. Dowling,et al. Verification, analytical validation, and clinical validation (V3): the foundation of determining fit-for-purpose for Biometric Monitoring Technologies (BioMeTs) , 2020, npj Digital Medicine.
[16] Amir Lerman,et al. Vocal Biomarker Is Associated With Hospitalization and Mortality Among Heart Failure Patients , 2020, Journal of the American Heart Association.
[17] Sridhar Krishnan,et al. Trends in audio signal feature extraction methods , 2020 .
[18] David C. Atkins,et al. Investigating voice as a biomarker: Deep phenotyping methods for early detection of Parkinson's disease , 2019, J. Biomed. Informatics.
[19] Elizabeth Shriberg,et al. Optimizing Speech-Input Length for Speaker-Independent Depression Classification , 2019, INTERSPEECH.
[20] Mohammad Soleymani,et al. AVEC 2019 Workshop and Challenge: State-of-Mind, Detecting Depression with AI, and Cross-Cultural Affect Recognition , 2019, AVEC@MM.
[21] Athanasios Tsanas,et al. Developing a large scale population screening tool for the assessment of Parkinson's disease using telephone-quality voice , 2019, The Journal of the Acoustical Society of America.
[22] C. Marmar,et al. Speech‐based markers for posttraumatic stress disorder in US veterans , 2019, Depression and anxiety.
[23] S. Adams,et al. Voice quality severity and responsiveness to levodopa in Parkinson's disease. , 2018, Journal of communication disorders.
[24] A. Tafreshi,et al. Speech disorders in Parkinson's disease: pathophysiology, medical management and surgical approaches. , 2018, Neurodegenerative disease management.
[25] Amir Lerman,et al. Voice Signal Characteristics Are Independently Associated With Coronary Artery Disease , 2018, Mayo Clinic proceedings.
[26] F. Martínez-Sánchez,et al. A Prototype for the Voice Analysis Diagnosis of Alzheimer's Disease. , 2018, Journal of Alzheimer's disease : JAD.
[27] Andrew Steptoe,et al. Effects of stress on the development and progression of cardiovascular disease , 2018, Nature Reviews Cardiology.
[28] Ryuki Tachibana,et al. Major depressive disorder discrimination using vocal acoustic features. , 2018, Journal of affective disorders.
[29] D. Mehta,et al. Acoustic speech analysis of patients with decompensated heart failure: A pilot study. , 2017, The Journal of the Acoustical Society of America.
[30] P. Santtila,et al. Investigating the Role of Salivary Cortisol on Vocal Symptoms. , 2017, Journal of speech, language, and hearing research : JSLHR.
[31] Andrew Steptoe,et al. Type 2 diabetes mellitus and psychological stress — a modifiable risk factor , 2017, Nature Reviews Endocrinology.
[32] Mitchell D. Wilkes,et al. Evaluation of Voice Acoustics as Predictors of Clinical Depression Scores. , 2017, Journal of voice : official journal of the Voice Foundation.
[33] Thomas F. Quatieri,et al. Detecting Depression using Vocal, Facial and Semantic Communication Cues , 2016, AVEC@ACM Multimedia.
[34] Fan Yang,et al. Depression Assessment by Fusing High and Low Level Features from Audio, Video, and Text , 2016, AVEC@ACM Multimedia.
[35] Jody Kreiman,et al. Comparing Measures of Voice Quality From Sustained Phonation and Continuous Speech. , 2016, Journal of speech, language, and hearing research : JSLHR.
[36] Eric J Topol,et al. State of Telehealth. , 2016, The New England journal of medicine.
[37] J. Bardram,et al. Voice analysis as an objective state marker in bipolar disorder , 2016, Translational psychiatry.
[38] R. Bianchi. Association between job strain and risk of incident stroke: A meta-analysis , 2016, Neurology.
[39] Ömer Eskidere,et al. Voice Disorder Classification Based on Multitaper Mel Frequency Cepstral Coefficients Features , 2015, Comput. Math. Methods Medicine.
[40] Kathleen C. Fraser,et al. Linguistic Features Identify Alzheimer's Disease in Narrative Speech. , 2015, Journal of Alzheimer's disease : JAD.
[41] Thomas F. Quatieri,et al. A review of depression and suicide risk assessment using speech analysis , 2015, Speech Commun..
[42] V. Manera,et al. Automatic speech analysis for the assessment of patients with predementia and Alzheimer's disease , 2015, Alzheimer's & dementia.
[43] C. Salisbury,et al. Telehealth interventions for primary prevention of cardiovascular disease: a systematic review and meta-analysis. , 2014, Preventive medicine.
[44] Grant Russell,et al. Accuracy of general practitioner unassisted detection of depression , 2014, The Australian and New Zealand journal of psychiatry.
[45] Hisashi Adachi,et al. Inflammation, atherosclerosis, and coronary artery disease. , 2005, The New England journal of medicine.
[46] P. Garrard,et al. Connected speech as a marker of disease progression in autopsy-proven Alzheimer’s disease , 2013, Brain : a journal of neurology.
[47] L. Sharp,et al. Traveling Towards Disease: Transportation Barriers to Health Care Access , 2013, Journal of Community Health.
[48] J. Mundt,et al. Vocal Acoustic Biomarkers of Depression Severity and Treatment Response , 2012, Biological Psychiatry.
[49] Francis L Martin,et al. Extracting biological information with computational analysis of Fourier-transform infrared (FTIR) biospectroscopy datasets: current practices to future perspectives. , 2012, The Analyst.
[50] E. Cuende,et al. The prevalence of dysphonia, its association with immunomediated diseases and correlation with biochemical markers. , 2012, Journal of voice : official journal of the Voice Foundation.
[51] S. Azar,et al. Vocal characteristics in patients with type 2 diabetes mellitus , 2012, European Archives of Oto-Rhino-Laryngology.
[52] Max A. Little,et al. Novel Speech Signal Processing Algorithms for High-Accuracy Classification of Parkinson's Disease , 2012, IEEE Transactions on Biomedical Engineering.
[53] Sharon M. Antonucci,et al. Anomia as a marker of distinct semantic memory impairments in Alzheimer's disease and semantic dementia. , 2011, Neuropsychology.
[54] F. Azizi,et al. Speech impairment in primary hypothyroidism , 2011, Journal of endocrinological investigation.
[55] M. Katzman,et al. Rates of detection of mood and anxiety disorders in primary care: a descriptive, cross-sectional study. , 2011, The primary care companion for CNS disorders.
[56] Yael Adini,et al. Abnormal Speech Spectrum and Increased Pitch Variability in Young Autistic Children , 2011, Front. Hum. Neurosci..
[57] Max A. Little,et al. Accurate Telemonitoring of Parkinson's Disease Progression by Noninvasive Speech Tests , 2009, IEEE Transactions on Biomedical Engineering.
[58] A. Smith,et al. Predicting the time of conversion to MCI in the elderly , 2009, Neurology.
[59] Douglas D. O'Shaughnessy,et al. Invited paper: Automatic speech recognition: History, methods and challenges , 2008, Pattern Recognit..
[60] Bernd Johannes,et al. Non-linear function model of voice pitch dependency on physical and mental load , 2007, European Journal of Applied Physiology.
[61] J. Mundt,et al. Voice acoustic measures of depression severity and treatment response collected via interactive voice response (IVR) technology , 2007, Journal of Neurolinguistics.
[62] Pedro Gómez Vilda,et al. Dimensionality Reduction of a Pathological Voice Quality Assessment System Based on Gaussian Mixture Models and Short-Term Cepstral Parameters , 2006, IEEE Transactions on Biomedical Engineering.
[63] K. Forbes-McKay,et al. Detecting subtle spontaneous language decline in early Alzheimer’s disease with a picture description task , 2005, Neurological Sciences.
[64] P. Snyder,et al. Variability in fundamental frequency during speech in prodromal and incipient Parkinson's disease: A longitudinal case study , 2004, Brain and Cognition.
[65] R W Barnes,et al. Cardiac autonomic function and incident coronary heart disease: a population-based case-cohort study. The ARIC Study. Atherosclerosis Risk in Communities Study. , 1997, American journal of epidemiology.
[66] P. Lieberman,et al. Fundamental frequency of phonation and perceived emotional stress. , 1997, The Journal of the Acoustical Society of America.
[67] D. Levy,et al. Impact of reduced heart rate variability on risk for cardiac events. The Framingham Heart Study. , 1996, Circulation.
[68] Joseph Picone,et al. Signal modeling techniques in speech recognition , 1993, Proc. IEEE.
[69] R F Orlikoff,et al. The relationship of age and cardiovascular health to certain acoustic characteristics of male voices. , 1990, Journal of speech and hearing research.
[70] Gábor Gosztolya,et al. A Speech Recognition-based Solution for the Automatic Detection of Mild Cognitive Impairment from Spontaneous Speech , 2018, Current Alzheimer research.
[71] H. Burr,et al. Effort-reward imbalance at work and incident coronary heart disease: a multi-cohort study of 90,164 individuals. , 2017, Epidemiology.
[72] Guigang Zhang,et al. Deep Learning , 2016, Int. J. Semantic Comput..