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Found 8 papers, 2 papers with code
Exploring the relationship between response time sequence in scale answering process and severity of insomnia: a machine learning approach
The relationship between symptom severity and response time was explored, and a machine learning model was developed to predict the presence of insomnia.
Attention-Based Acoustic Feature Fusion Network for Depression Detection
To rectify this, we present the novel Attention-Based Acoustic Feature Fusion Network (ABAFnet) for depression detection.
Adaptive control of dynamic networks
However, the efficacy of the incumbent MDS may diminish as the network topologies evolve.
NetMoST: A network-based machine learning approach for subtyping schizophrenia using polygenic SNP allele biomarkers
Subtyping neuropsychiatric disorders like schizophrenia is essential for improving the diagnosis and treatment of complex diseases.
Identification of cancer-keeping genes as therapeutic targets by finding network control hubs
One of the recent approaches is based on network structural controllability that focuses on finding a control scheme and driver genes that can steer the cell from an arbitrary state to a designated state.
Response to: Significance and stability of deep learning-based identification of subtypes within major psychiatric disorders. Molecular Psychiatry (2022)
They questioned the generalizability of our methods and the statistical significance, stability, and overfitting of the results, and proposed a pipeline for disease subtyping.
Total controllability analysis discovers explainable drugs for Covid-19 treatment
One such approach adopts structural controllability, a theory for controlling a network (the cell).
An efficient algorithm for finding all possible input nodes for controlling complex networks
The main idea is to modify a maximum matching algorithm to make it efficient for finding all possible input nodes by computing only one MIS.
Discrete Mathematics Social and Information Networks Physics and Society
