Best Machine Learning Results on Test Set.

<p>Best Machine Learning Results on Test Set.</p

Rule Based Results

<p>Rule Based Results</p

ASD Rule-based Algorithm.

<p>ASD–Autism Spectrum Disorder; EHR–Electronic Health Records; ICD-9 –International Classification of Diseases 9^th edition; DSM IV–Diagnostic and Statistical Manual of Mental Diseases 4^th edition; PDD-NOS–pervasive developmental disorder not otherwise specified; sections 3a., 3b., 3c. refer to DSM IV ASD classification for Autism, Asperger’s and PDD-NOS, respectively</p

Baseline Results (ICD-9 codes) on Test Set.

<p>Baseline Results (ICD-9 codes) on Test Set.</p

Dimensionality reduction using the t-SNE algorithm on PheWAS codes.

<p>Colors label clusters from the k-means algorithm. The clusters are labeled according to the comorbidity category with the highest relative prevalence for that cluster—duplicate labels appear when there is more than one cluster dominated by the same category. (t-distributed Stochastic Neighbor Embedding—t-SNE, Phenotype Wide Association Study–PheWAS, BCH–Boston Children’s Hospital; CCHMC–Cincinnati’s Children’s Hospital and Medical Center; VUMC–Vanderbilt University Medical Center, Deve.–Developmental Disorders, Seiz.–Seizure Disorders, Psych.—Psychological Disorders).</p

ASD Algorithm Project Overview.

<p>ASD–Autism Spectrum Disorder; ICD-9 –International Classification of Diseases 9^th edition; DSM IV–Diagnostic and Statistical Manual of Mental Diseases 4^th edition; ML—machine learning</p

Distribution of patients

<p>Distribution of patients</p

SVM-based Machine Learning Prediction System.

<p>SVM–Support Vector Machines.</p

Comparison of relative prevalence of primary co-morbidity categories for clusters of NLP rule-based patients for BCH, and CCHMC and VUMC.

<p>BCH–Boston Children’s Hospital; CCHMC–Cincinnati Children’s Hospital and Medical Center; VUMC–Vanderbilt University Medical Center.</p