Biomarkers are objective indicators based on biological measurements. The development of biomarkers will contribute to a deeper understanding and stratified medicine of psychiatric disorders. Until now, many types of biomarkers such as molecular, protein, physiological and psychoradiological activity including brain activity have been developed. In particular, omics such as genomics, metabolomics, and lipidomics, have been attracting attention in the field. The development of measurement technologies and smart devices makes it possible to obtain various biological indicators. On the other hand, the analysis technology of the multi-modal large-scale data has been developed as well. More specifically, machine learning and AI enable us to uncover the relationship between psychiatric disorders and biomarkers and predict the diagnosis and response to treatment.
The goal of this research topic is to facilitate the development of biomarkers for psychiatric disorders. To this end, we will cover all types of biomarker studies for psychiatric disorders including molecular, anatomical, and physiological studies. Developments of measurement technologies and analysis methods will also be featured. The integration of these approaches would promote the discovery of biomarkers that can predict the diagnosis and response to treatment of a psychiatric disorder.
We will welcome original studies and reviews covering the following topics:
-Machine-learning methods to handle the biological data of psychiatric disorder
-Novel methods to measure biological indicators for a psychiatric disorder
-Molecular biomarker development for a psychiatric disorder
-Physiological or psychoradiological biomarker of the brain for a psychiatric disorder
Biomarkers are objective indicators based on biological measurements. The development of biomarkers will contribute to a deeper understanding and stratified medicine of psychiatric disorders. Until now, many types of biomarkers such as molecular, protein, physiological and psychoradiological activity including brain activity have been developed. In particular, omics such as genomics, metabolomics, and lipidomics, have been attracting attention in the field. The development of measurement technologies and smart devices makes it possible to obtain various biological indicators. On the other hand, the analysis technology of the multi-modal large-scale data has been developed as well. More specifically, machine learning and AI enable us to uncover the relationship between psychiatric disorders and biomarkers and predict the diagnosis and response to treatment.
The goal of this research topic is to facilitate the development of biomarkers for psychiatric disorders. To this end, we will cover all types of biomarker studies for psychiatric disorders including molecular, anatomical, and physiological studies. Developments of measurement technologies and analysis methods will also be featured. The integration of these approaches would promote the discovery of biomarkers that can predict the diagnosis and response to treatment of a psychiatric disorder.
We will welcome original studies and reviews covering the following topics:
-Machine-learning methods to handle the biological data of psychiatric disorder
-Novel methods to measure biological indicators for a psychiatric disorder
-Molecular biomarker development for a psychiatric disorder
-Physiological or psychoradiological biomarker of the brain for a psychiatric disorder
