AIMC Topic: Periodontal Diseases

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Exploring Genome-Wide Expression Profiles Using Machine Learning Techniques.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2017
Although contemporary high-throughput -omics methods produce high-dimensional data, the resulting wealth of information is difficult to assess using traditional statistical procedures. Machine learning methods facilitate the detection of additional p...
Humans Machine Learning Software Algorithms Phenotype Gene Expression Profiling Transcriptome Genome-Wide Association Study Genomics Computational Biology Cluster Analysis Periodontitis Periodontal Diseases Gene Expression Regulation
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Diagnosis of periodontal diseases using different classification algorithms: a preliminary study.

Nigerian journal of clinical practice Jan 1, 2015
OBJECTIVE: The purpose of the proposed study was to develop an identification unit for classifying periodontal diseases using support vector machine (SVM), decision tree (DT), and artificial neural networks (ANNs).
Humans Female Risk Factors Young Adult Adult Male Middle Aged Diagnosis, Computer-Assisted Adolescent Support Vector Machine Decision Trees Radiography Periodontal Diseases
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