AI Medical Compendium Journal:
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing

Showing 71 to 76 of 76 articles

Mapping Patient Trajectories using Longitudinal Extraction and Deep Learning in the MIMIC-III Critical Care Database.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing Jan 1, 2018
Electronic Health Records (EHRs) contain a wealth of patient data useful to biomedical researchers. At present, both the extraction of data and methods for analyses are frequently designed to work with a single snapshot of a patient's record. Health ...
Electronic Health Records Female Machine Learning Databases, Factual Unsupervised Machine Learning Supervised Machine Learning Critical Care Male Computational Biology Humans
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PREDICTIVE MODELING OF HOSPITAL READMISSION RATES USING ELECTRONIC MEDICAL RECORD-WIDE MACHINE LEARNING: A CASE-STUDY USING MOUNT SINAI HEART FAILURE COHORT.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing Jan 1, 2017
Reduction of preventable hospital readmissions that result from chronic or acute conditions like stroke, heart failure, myocardial infarction and pneumonia remains a significant challenge for improving the outcomes and decreasing the cost of healthca...
Models, Statistical Bayes Theorem Cohort Studies Computational Biology New York City Heart Failure Patient Readmission Humans Machine Learning Algorithms Electronic Health Records
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DEEP MOTIF DASHBOARD: VISUALIZING AND UNDERSTANDING GENOMIC SEQUENCES USING DEEP NEURAL NETWORKS.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing Jan 1, 2017
Deep neural network (DNN) models have recently obtained state-of-the-art prediction accuracy for the transcription factor binding (TFBS) site classification task. However, it remains unclear how these approaches identify meaningful DNA sequence signa...
Humans Neural Networks, Computer Databases, Genetic DNA Binding Sites Genome, Human Models, Genetic Transcription Factors Genomics Computational Biology
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INSIGHTS FROM MACHINE-LEARNED DIET SUCCESS PREDICTION.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing Jan 1, 2016
To support people trying to lose weight and stay healthy, more and more fitness apps have sprung up including the ability to track both calories intake and expenditure. Users of such apps are part of a wider "quantified self" movement and many opt-in...
Data Mining Energy Metabolism Diet Records Weight Reduction Programs Diet, Reducing Computational Biology Cluster Analysis Energy Intake Mobile Applications Humans Machine Learning Algorithms
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KNOWLEDGE-ASSISTED APPROACH TO IDENTIFY PATHWAYS WITH DIFFERENTIAL DEPENDENCIES.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing Jan 1, 2016
We have previously developed a statistical method to identify gene sets enriched with condition-specific genetic dependencies. The method constructs gene dependency networks from bootstrapped samples in one condition and computes the divergence betwe...
Gene Regulatory Networks Computational Biology Databases, Genetic Models, Statistical Signal Transduction Brain Neoplasms Gene Expression Profiling Likelihood Functions Humans Systems Integration Glioblastoma Algorithms Knowledge Bases
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Machine learning from concept to clinic: reliable detection of BRAF V600E DNA mutations in thyroid nodules using high-dimensional RNA expression data.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing Jan 1, 2015
The promise of personalized medicine will require rigorously validated molecular diagnostics developed on minimally invasive, clinically relevant samples. Measurement of DNA mutations is increasingly common in clinical settings but only higher-preval...
Computational Biology DNA, Neoplasm Support Vector Machine Gene Expression Profiling Oligonucleotide Array Sequence Analysis Proto-Oncogene Proteins B-raf Mutation Thyroid Nodule DNA Mutational Analysis RNA, Neoplasm High-Throughput Nucleotide Sequencing Biopsy, Fine-Needle Humans Machine Learning
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