YOU(th) | Research

Face Video Technology

Estimating Blood Pressure from the Photoplethysmogramy Signal and Demographic Features Using Machine Learning Techniques

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Face Video Technology

Cardiovascular assessment by imaging photoplethysmography

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Face Video Technology

MX Labs accuracy report

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Face Video Technology

Smartphone camera based assessment of adiposity: a validation study

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Face Video Technology

A deep learning model for novel systemic biomarkers in photographs of the external eye: a retrospective study

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Face Video Technology

Detection of signs of disease in external photographs of the eyes via deep learning

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Face Video Technology

PhotoAgeClock: Deep learning algorithms for development of noninvasive visual biomarkers of aging

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Face Video Technology

Deep-Learning-Based Smartphone Application for Self-Diagnosis of Scleral Jaundice in Patients with Hepatobiliary and Pancreatic Diseases

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Face Video Technology

A deep learning model for novel systemic biomarkers in photographs of the external eye: a retrospective study

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Face Video Technology

Eye diseases classification using deep learning

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Voice recording technology

Predicting dementia from spontaneous speech using large language models

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Voice recording technology

Detecting Alzheimer’s Disease in a Call Center Using Vocal Biomarkers

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Voice recording technology

Harnessing acoustic speech parameters to decipher amyloid status in individuals with mild cognitive impairment

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Voice recording technology

Development and Validation of a Respiratory-Responsive Vocal Biomarker–Based Tool for Generalizable Detection of Respiratory Impairment

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Voice recording technology

Feasibility of a Machine Learning-Based Smartphone Application in Detecting Depression and Anxiety in a Generally Senior Population

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Voice recording technology

Robust Speech and Natural Language Processing Models for Depression Screening

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Voice recording technology

Cross-Demographic Portability of Deep NLP-Based Depression Models

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Voice recording technology

Temporal Integration of Text Transcripts and Acoustic Features for Alzheimer's Diagnosis Based on Spontaneous Speech

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Voice recording technology

Speech-Based Depression Prediction using Encoder-Weight-Only Transfer Learning and a Large Corpus

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Skin phototechnology

Generalization of Deep Acoustic and NLP Models for Large-Scale Depression Screening (Chapter 3 from the book Biomedical Sensing and Analysis)

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The Research

Estimating Blood Pressure from the Photoplethysmogramy Signal and Demographic Features Using Machine Learning Techniques

Cardiovascular assessment by imaging photoplethysmography

MX Labs accuracy report

Smartphone camera based assessment of adiposity: a validation study

A deep learning model for novel systemic biomarkers in photographs of the external eye: a retrospective study

Detection of signs of disease in external photographs of the eyes via deep learning

PhotoAgeClock: Deep learning algorithms for development of noninvasive visual biomarkers of aging

Deep-Learning-Based Smartphone Application for Self-Diagnosis of Scleral Jaundice in Patients with Hepatobiliary and Pancreatic Diseases

A deep learning model for novel systemic biomarkers in photographs of the external eye: a retrospective study

Eye diseases classification using deep learning

Predicting dementia from spontaneous speech using large language models

Detecting Alzheimer’s Disease in a Call Center Using Vocal Biomarkers

Harnessing acoustic speech parameters to decipher amyloid status in individuals with mild cognitive impairment

Development and Validation of a Respiratory-Responsive Vocal Biomarker–Based Tool for Generalizable Detection of Respiratory Impairment

Feasibility of a Machine Learning-Based Smartphone Application in Detecting Depression and Anxiety in a Generally Senior Population

Robust Speech and Natural Language Processing Models for Depression Screening

Cross-Demographic Portability of Deep NLP-Based Depression Models

Temporal Integration of Text Transcripts and Acoustic Features for Alzheimer's Diagnosis Based on Spontaneous Speech

Speech-Based Depression Prediction using Encoder-Weight-Only Transfer Learning and a Large Corpus

Generalization of Deep Acoustic and NLP Models for Large-Scale Depression Screening (Chapter 3 from the book Biomedical Sensing and Analysis)

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