Applications of unsupervised machine learning in autism spectrum disorder research: a review
CM Parlett-Pelleriti, E Stevens, D Dixon… - Review Journal of Autism …, 2023 - Springer
Large amounts of autism spectrum disorder (ASD) data is created through hospitals, therapy
centers, and mobile applications; however, much of this rich data does not have pre-existing …
centers, and mobile applications; however, much of this rich data does not have pre-existing …
[HTML][HTML] How do they pay as they go?: Learning payment patterns from solar home system users data in Rwanda and Kenya
Abstract Pay-as-you-go (PAYGo) financing models play a vital role in boosting the
distribution of solar-home-systems (SHSs) to electrify rural Sub-Saharan Africa. This …
distribution of solar-home-systems (SHSs) to electrify rural Sub-Saharan Africa. This …
An explainable and statistically validated ensemble clustering model applied to the identification of traumatic brain injury subgroups
We present a framework for an explainable and statistically validated ensemble clustering
model applied to Traumatic Brain Injury (TBI). The objective of our analysis is to identify …
model applied to Traumatic Brain Injury (TBI). The objective of our analysis is to identify …
Heterogeneity in blood biomarker trajectories after mild TBI revealed by unsupervised learning
LA Bui, D Yeboah, L Steinmeister… - … ACM transactions on …, 2021 - ieeexplore.ieee.org
Concussions, also known as mild traumatic brain injury (mTBI), are a growing health
challenge. Approximately four million concussions are diagnosed annually in the United …
challenge. Approximately four million concussions are diagnosed annually in the United …
Applications of node-based resilience graph theoretic framework to clustering autism spectrum disorders phenotypes
With the growing ubiquity of data in network form, clustering in the context of a network,
represented as a graph, has become increasingly important. Clustering is a very useful data …
represented as a graph, has become increasingly important. Clustering is a very useful data …
Connecting phenotype to genotype: PheWAS-inspired analysis of autism spectrum disorder
Autism Spectrum Disorder (ASD) is extremely heterogeneous clinically and genetically.
There is a pressing need for a better understanding of the heterogeneity of ASD based on …
There is a pressing need for a better understanding of the heterogeneity of ASD based on …
Multiple Imputation for Robust Cluster Analysis to Address Missingness in Medical Data
Cluster analysis has been applied to a wide range of problems as an exploratory tool to
enhance knowledge discovery. Clustering aids disease subtyping, ie identifying …
enhance knowledge discovery. Clustering aids disease subtyping, ie identifying …