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Found 6 papers, 2 papers with code
AC-EVAL: Evaluating Ancient Chinese Language Understanding in Large Language Models
Given the importance of ancient Chinese in capturing the essence of rich historical and cultural heritage, the rapid advancements in Large Language Models (LLMs) necessitate benchmarks that can effectively evaluate their understanding of ancient contexts.
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.
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.
Total controllability analysis discovers explainable drugs for Covid-19 treatment
One such approach adopts structural controllability, a theory for controlling a network (the cell).
