The TUH EEG CORPUS: A big data resource for automated EEG interpretation

Amir Harati, S. Lopez, Iyad Obeid, +3

EngineeringMachine LearningMachine Learning ToolNeurolinguisticsLarge-scale Datasets +18

Improved EEG event classification using differential energy

Amir Harati, Meysam Golmohammadi, S. Lopez, +2

Detecting Paroxysmal Coughing from Pertussis Cases Using Voice Recognition Technology

Danny Parker, J. Picone, Amir Harati, +3

PLoS ONE

The Temple University Hospital EEG corpus

Amir Harati, Soon-Wook Choi, M.H.N. Tabrizi, +3

Pilot DatabaseMachine LearningEngineeringMachine Learning ToolNeurolinguistics +16

Depression and Anxiety Prediction Using Deep Language Models and Transfer Learning

Tomasz Rutowski, Elizabeth Shriberg, Amir Harati, +3

Monitoring ApplicationsEngineeringSpeech CorpusSpoken Language ProcessingMental Health +20

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

David Lin, Tahmida Nazreen, Tomasz Rutowski, +5

Frontiers in Psychology

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

Amir Harati, Elizabeth Shriberg, Tomasz Rutowski, +3

Large CorpusEngineeringMachine LearningSpeech-based AlgorithmsSpeech Recognition +17

Optimizing Speech-Input Length for Speaker-Independent Depression Classification

Tomasz Rutowski, Amir Harati, Yang Lü, +1

Speech AnalysisHealth SciencesPsychiatryDepressionRobust Speech Recognition +7

Cross-Demographic Portability of Deep NLP-Based Depression Models

Tomek Rutowski, Elizabeth Shriberg, Amir Harati, +3