Skip to main navigation
Skip to search
Skip to main content
New Jersey Institute of Technology Home
Help & FAQ
Home
Profiles
Research units
Facilities
Federal Grants
Research output
Press/Media
Search by expertise, name or affiliation
Machine learning derived risk prediction of anorexia nervosa
Yiran Guo
,
Zhi Wei
, Brendan J. Keating
, Hakon Hakonarson
Research output
:
Contribution to journal
›
Article
›
peer-review
22
Scopus citations
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'Machine learning derived risk prediction of anorexia nervosa'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Keyphrases
Anorexia Nervosa
100%
Applied Machine Learning
12%
Area under the Receiver Operating Characteristic Curve
12%
AUC Value
12%
Children's Hospital
12%
Clinical Setting
12%
Collaborative Groups
12%
Control Subjects
12%
Disease Risk
25%
Family-centered
12%
Genetic Contribution
12%
Genome-wide Association Study
12%
Genome-wide Genotyping
12%
Genomic Data
12%
Genotype
12%
Gradient Boosted Trees
12%
Gradient Vector
12%
Lasso Penalty
12%
Logistic Regression Model
12%
Machine Learning
100%
Machine Learning Models
12%
Machine Learning Techniques
25%
Penalty Method
12%
Performance Prediction
12%
Philadelphia
12%
Process Evaluation
12%
Psychiatric Disease
12%
Risk Evaluation
12%
Risk Prediction
100%
Risky Driving
12%
Support Vector Machine
12%
Wellcome Trust Case Control Consortium
12%
Biochemistry, Genetics and Molecular Biology
Environmental Genomics
33%
Genetics
100%
Genome-Wide Association Study
33%
Genotyping
66%
Sample Size
33%
Support Vector Machine
33%
Tree
33%
Medicine and Dentistry
Anorexia Nervosa
100%
Disease
25%
Genome Wide Association Study
12%
Genotype
12%
Logistic Regression Analysis
12%
Risk Evaluation
12%
Neuroscience
Anorexia Nervosa
100%
Genome-Wide Association Study
12%
Support Vector Machine
12%