The braingraphs were computed by using the CMTK suite (Daducci et al.2012), with the details given in the beginning of the section. The figures were created by using Python Matplotlib mplot3D and Networkx packages. The 1950-dimensional SVM was computed using the Python Scikit-Learn suite of...
Supplementary Text and Figures Supplementary Tables 1–3 (PDF 289 kb) Supplementary Methods Checklist (PDF 421 kb) About this article Cite this article Finn, E., Shen, X., Scheinost, D.et al.Functional connectome fingerprinting: identifying individuals using patterns of brain connectivity.Nat Neur...
There are several issues that could cause the inaccuracy in separating these groups: the complexity of the multi-group classification problem, the difficulty of high-dimensional biological measures in representing the clinical symptoms, and the inherent unreliability of the clinically determined diagnosis ...
Anatomical whole-brain image volumes were determined using a sagittal magnetization-prepared rapid acquisition gradient-echo three-dimensional T1-weighted sequence (repetition time [TR] = 2530 ms, echo time [TE] = 3 ms, echo spacing = 7.25 ms, flip angle [FA] = 7 degrees,...
Application of Three-Dimensional Fluorescence Spectroscopy in Smart Agriculture - Detection of Oil Pollutants in Water 2023, International Journal of Pattern Recognition and Artificial Intelligence Determination of oil pollutants by three-dimensional fluorescence spectroscopy combined with improved pattern recognitio...
Here we introduce a longlist of nine candidate states used in legged locomotion and the way to measure or estimate them on a real robot: (1) base position in the world frame that can be estimated using visual inertial odometry55, the three-dimensional base position was used rather than the...
statistical methods, such as Akaike information criterion (AIC) and Bayesian information criterion (BIC), penalize the number of parameters in the model, but they need to screen all the subsets of the parameters, which is infeasible in terms of computational complexity in high-dimensional data. LA...
The results are shown in Figures S2-S6 of Additional File [see Additional file 1]. As can be seen from Figure S2, 30 wards of Hokkaido were modelled as a 30-node city network. Figure S3 shows that there were seven seasonal normal outbreaks and three large-scale outbreaks of HFMD in ...
Automated syndrome diagnosis by three-dimensional facial imaging Article Open access 01 June 2020 PhenoScore quantifies phenotypic variation for rare genetic diseases by combining facial analysis with other clinical features using a machine-learning framework Article 07 August 2023 Using deep-neural...
Supplementary Figures S10–S13 and Tables S6 and S7 summarize the performance of IMPALA versus three competing algorithms: random color coding12, edge orientation15, and integer linear programming (ILP)10. Note that we only applied ILP to pathway gene identification because ILP does not infer signa...