3 papers
cs.LG2023
A New Deep State-Space Analysis Framework for Patient Latent State Estimation and Classification from EHR Time Series Data
Aya Nakamura, Ryosuke Kojima, Yuji Okamoto +7
Many diseases, including cancer and chronic conditions, require extended treatment periods and long-term strategies. Machine learning and AI research focusing on electronic health…
q-bio.QM2023
An end-to-end framework for gene expression classification by integrating a background knowledge graph: application to cancer prognosis prediction
Kazuma Inoue, Ryosuke Kojima, Mayumi Kamada +1
Biological data may be separated into primary data, such as gene expression, and secondary data, such as pathways and protein-protein interactions. Methods using secondary data to…
cs.LG2022
GraphIX: Graph-based In silico XAI(explainable artificial intelligence) for drug repositioning from biopharmaceutical network
Atsuko Takagi, Mayumi Kamada, Eri Hamatani +2
Drug repositioning holds great promise because it can reduce the time and cost of new drug development. While drug repositioning can omit various R&D processes, confirming pharmaco…