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Factors Determining Acceptance of Internet of Things in Medical Education: Mixed Methods Study

Factors Determining Acceptance of Internet of Things in Medical Education: Mixed Methods Study

The analysis uses a hybrid framework that combines structural equation modeling (SEM) and artificial neural networks (ANN) to examine how intrinsic motivational factors and perceived technological attributes affect Io T adoption. The SEM-ANN approach was specifically chosen to leverage the strengths of both methodologies [9,10].

Khadija Alhumaid, Kevin Ayoubi, Maha Khalifa, Said Salloum

JMIR Hum Factors 2025;12:e58377

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Estimating the Prevalence of Schizophrenia in the General Population of Japan Using an Artificial Neural Network–Based Schizophrenia Classifier: Web-Based Cross-Sectional Survey

Estimating the Prevalence of Schizophrenia in the General Population of Japan Using an Artificial Neural Network–Based Schizophrenia Classifier: Web-Based Cross-Sectional Survey

In our previous research, we developed an artificial neural network (ANN)–based schizophrenia classification model (SZ classifier) to classify schizophrenia cases in the Japanese population and verified its generalizability [14]. The model was trained by using data from a large-scale Japanese web-based survey; the presence of schizophrenia served as a response variable.

Pichsinee Choomung, Yupeng He, Masaaki Matsunaga, Kenji Sakuma, Taro Kishi, Yuanying Li, Shinichi Tanihara, Nakao Iwata, Atsuhiko Ota

JMIR Form Res 2025;9:e66330

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