首页|New Study Findings from University of Sevilla Illuminate Research in Machine Lea rning (Optimized Machine Learning Classifiers for Symptom-Based Disease Screenin g)
New Study Findings from University of Sevilla Illuminate Research in Machine Lea rning (Optimized Machine Learning Classifiers for Symptom-Based Disease Screenin g)
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New research on artificial intelligenc e is the subject of a new report. According to news reporting from Seville, Spai n, by NewsRx journalists, research stated, "This work presents a disease detecti on classifier based on symptoms encoded by their severity." Funders for this research include Ministerio De Ciencia, Innovacion Y Universida des (Spanish Government): Spanish Aei (Agencia Estatal De Investigacion) Project Adicvideo. Our news journalists obtained a quote from the research from University of Sevil la: "This model is presented as part of the solution to the saturation of the he althcare system, aiding in the initial screening stage. An open-source dataset i s used, which undergoes pre-processing and serves as the data source to train an d test various machine learning models, including SVM, RFs, KNN, and ANNs. A thr ee-phase optimization process is developed to obtain the best classifier: first, the dataset is pre-processed; secondly, a grid search is performed with several hyperparameter variations to each classifier; and, finally, the best models obt ained are subjected to additional filtering processes. The best-results model, s elected based on the performance and the execution time, is a KNN with 2 neighbo rs, which achieves an accuracy and F1 score of over 98%."
University of SevillaSevilleSpainE uropeCyborgsEmerging TechnologiesMachine Learning
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