Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1007/s00702-020-02144-8 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Feasibility of Mental Health Triage Call Priority Prediction Using Machine Learning.
Nurs Rep
December 2024
Mental Health and Specialist Services, West Moreton Health, Brisbane, QLD 4076, Australia.
Background: Optimum efficiency and responsiveness to callers of mental health helplines can only be achieved if call priority is accurately identified. Currently, call operators making a triage assessment rely heavily on their clinical judgment and experience. Due to the significant morbidity and mortality associated with mental illness, there is an urgent need to identify callers to helplines who have a high level of distress and need to be seen by a clinician who can offer interventions for treatment.
View Article and Find Full Text PDFStructural-functional connectivity decoupling in multiscale brain networks in Parkinson's disease.
BMC Neurosci
December 2024
The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, P.R. China.
Background: Parkinson's disease (PD) is a progressive neurodegenerative disease associated with functional and structural alterations beyond the nigrostriatal dopamine projection. However, the structural-functional (SC-FC) coupling changes in combination with subcortical regions at the network level are rarely investigated in PD.
Methods: SC-FC coupling networks were systematically constructed using the structural connectivity obtained by diffusion tensor imaging and the functional connectivity obtained by resting-state functional magnetic resonance imaging in 53 PD and 72 age- and sex-matched healthy controls (HCs).
Evaluations of the Perturbation Resistance of the Deep-Learning-Based Ligand Conformation Optimization Algorithm.
J Chem Inf Model
December 2024
School of Physics, Shandong University, Jinan 250100, China.
In recent years, the deep learning (DL) technique has rapidly developed and shown great success in scoring the protein-ligand binding affinities. The protein-ligand conformation optimization based on DL-derived scoring functions holds broad application prospects, for instance, drug design and enzyme engineering. In this study, we evaluated the robustness of a DL-based ligand conformation optimization protocol (DeepRMSD+Vina) for optimizing structures with input perturbations by examining the predicted ligand binding poses and scoring.
View Article and Find Full Text PDFEvidence of compensatory neural hyperactivity in a subgroup of breast cancer survivors treated with chemotherapy and its association with brain aging.
Front Aging Neurosci
December 2024
Division of Adult Health, School of Nursing, University of Texas at Austin, Austin, TX, United States.
Introduction: Chemotherapy-related cognitive impairment (CRCI) remains poorly understood in terms of the mechanisms of cognitive decline. Neural hyperactivity has been reported on average in cancer survivors, but it is unclear which patients demonstrate this neurophenotype, limiting precision medicine in this population.
Methods: We evaluated a retrospective sample of 80 breast cancer survivors and 80 non-cancer controls, aged 35-73, for which we had previously identified and validated three data-driven, biological subgroups (biotypes) of CRCI.
Want AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!