Deep ensemble learning for Alzheimers disease classification

no code implementations • 30 May 2019 • Ning An, Huitong Ding, Jiaoyun Yang, Rhoda Au, Ting Fang Alvin Ang

The proposed deep ensemble learning framework is used for Alzheimers disease classification.

Classification Ensemble Learning +1

Role-specific Language Models for Processing Recorded Neuropsychological Exams

no code implementations • NAACL 2018 • Tuka Al Hanai, Rhoda Au, James Glass

Neuropsychological examinations are an important screening tool for the presence of cognitive conditions (e. g. Alzheimer{'}s, Parkinson{'}s Disease), and require a trained tester to conduct the exam through spoken interactions with the subject.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +3

Spoken Language Biomarkers for Detecting Cognitive Impairment

1 code implementation • 20 Oct 2017 • Tuka Alhanai, Rhoda Au, James Glass

In this study we developed an automated system that evaluates speech and language features from audio recordings of neuropsychological examinations of 92 subjects in the Framingham Heart Study.

Interpretable Machine Learning Models for the Digital Clock Drawing Test

no code implementations • 23 Jun 2016 • William Souillard-Mandar, Randall Davis, Cynthia Rudin, Rhoda Au, Dana Penney

The Clock Drawing Test (CDT) is a rapid, inexpensive, and popular neuropsychological screening tool for cognitive conditions.

BIG-bench Machine Learning Interpretable Machine Learning