PROVIDING INTELLIGENT SOFTWARE TO DIAGNOSE THE TYPE AND SEVERITY OF MENTAL DISORDERS BASED ON QEEG: A COMPARATIVE STUDY BETWEEN THE STATISTICAL METHOD AND THE INTELLIGENT METHOD

Background: Identifying mental disorder biomarkers is one of the leading goals of the clinical science.Objectives: This study aimed to provide an artificial intelligence based solution and software program to diagnose the type and severity of mental disorders according to the quantitative electroencephalogram (QEEG) of patients.Materials and Method

From the perspective of project and paper datasets, research frontier recognition in the field of agricultural resources and the environment using the Latent Dirichlet Allocation (LDA) topic extraction model was studied.By combining the wisdom of domain experts to judge the similarities and differences of clustering topics between the two data sour

Kawango Agot,1 Alexandra M Minnis,2 Kgahlisho Manenzhe,3 Erica N Browne,2 Khatija Ahmed,3 Timothy Okello,1 Ariane van der Straten21Impact Research and Development Organization, Kisumu, Kenya; 2Women’s Global Health Imperative, RTI International, San Francisco, CA, USA; 3Setshaba Research Centre, Soshanguve, South AfricaBackground: Women accou

In the field of pervasive computing, wearable devices have been widely used for recognizing human activities.One important area in this research is the recognition of activities of daily living where especially inertial sensors and interaction sensors (like RFID tags with scanners) are popular choices as data sources.Using interaction sensors, howe

In general, the chloroplast genomes of angiosperms are considered to be highly conserved and affected little by adaptive evolution.In this study, we tested this hypothesis based on sequence differentiation and adaptive variation in the plastid genomes in the Hemp Wicks order Dipsacales.We sequenced the plastid genomes of one Adoxaceae species and s