A review of and roadmap for data science and machine learning for the neuropsychiatric phenotype of autism
P Washington, DP Wall - Annual review of biomedical data …, 2023 - annualreviews.org
Autism spectrum disorder (autism) is a neurodevelopmental delay that affects at least 1 in 44
children. Like many neurological disorder phenotypes, the diagnostic features are …
children. Like many neurological disorder phenotypes, the diagnostic features are …
Challenges and opportunities for machine learning classification of behavior and mental state from images
P Washington, CO Mutlu, A Kline, K Paskov… - arXiv preprint arXiv …, 2022 - arxiv.org
Computer Vision (CV) classifiers which distinguish and detect nonverbal social human
behavior and mental state can aid digital diagnostics and therapeutics for psychiatry and the …
behavior and mental state can aid digital diagnostics and therapeutics for psychiatry and the …
Individualized stress mobile sensing using self-supervised pre-training
T Islam, P Washington - Applied Sciences, 2023 - mdpi.com
Stress is widely recognized as a major contributor to a variety of health issues. Stress
prediction using biosignal data recorded by wearables is a key area of study in mobile …
prediction using biosignal data recorded by wearables is a key area of study in mobile …
[HTML][HTML] The classification of abnormal hand movement to aid in autism detection: Machine learning study
A Lakkapragada, A Kline, OC Mutlu… - JMIR Biomedical …, 2022 - biomedeng.jmir.org
Background A formal autism diagnosis can be an inefficient and lengthy process. Families
may wait several months or longer before receiving a diagnosis for their child despite …
may wait several months or longer before receiving a diagnosis for their child despite …
[HTML][HTML] Training and profiling a pediatric facial expression classifier for children on mobile devices: machine learning study
Background Implementing automated facial expression recognition on mobile devices could
provide an accessible diagnostic and therapeutic tool for those who struggle to recognize …
provide an accessible diagnostic and therapeutic tool for those who struggle to recognize …
[HTML][HTML] Identification of social engagement indicators associated with autism spectrum disorder using a game-based mobile app: comparative study of gaze fixation …
Background Autism spectrum disorder (ASD) is a widespread neurodevelopmental
condition with a range of potential causes and symptoms. Standard diagnostic mechanisms …
condition with a range of potential causes and symptoms. Standard diagnostic mechanisms …
Personalization of stress mobile sensing using self-supervised learning
T Islam, P Washington - arXiv preprint arXiv:2308.02731, 2023 - arxiv.org
Stress is widely recognized as a major contributor to a variety of health issues. Stress
prediction using biosignal data recorded by wearables is a key area of study in mobile …
prediction using biosignal data recorded by wearables is a key area of study in mobile …
Machine learning models using mobile game play accurately classify children with autism
N Deveau, P Washington, E Leblanc, A Husic… - Intelligence-Based …, 2022 - Elsevier
Digitally-delivered healthcare is well suited to address current inequities in the delivery of
care due to barriers of access to healthcare facilities. As the COVID-19 pandemic phases …
care due to barriers of access to healthcare facilities. As the COVID-19 pandemic phases …
Training affective computer vision models by crowdsourcing soft-target labels
P Washington, H Kalantarian, J Kent, A Husic… - Cognitive …, 2021 - Springer
Emotion detection classifiers traditionally predict discrete emotions. However, emotion
expressions are often subjective, thus requiring a method to handle compound and …
expressions are often subjective, thus requiring a method to handle compound and …
[HTML][HTML] A Perspective on Crowdsourcing and Human-in-the-Loop Workflows in Precision Health
P Washington - Journal of Medical Internet Research, 2024 - jmir.org
Modern machine learning approaches have led to performant diagnostic models for a
variety of health conditions. Several machine learning approaches, such as decision trees …
variety of health conditions. Several machine learning approaches, such as decision trees …