Listening study perceptual ratings. by Stefan K. Ehrlich (6475490)

Classification accuracy and information transfer rate (ITR) as a function of the measurement set-up and the number of combined trials. by Dovilė Kurmanavičiūtė (21072549)

Correlation analysis results. by Stefan K. Ehrlich (6475490)

Listening study results. by Stefan K. Ehrlich (6475490)

Analyses of Immune microenvironment and functions between gene clusters by Jiangli Zhao (2308330)

Analyses of Immune microenvironment and functions between m7G clusters. by Jiangli Zhao (2308330)

Comparison of CFC inference by GC, DPGM, PCMCI-GPDC and selVAR, and TPC on benchmarking datasets. For each dataset, each method’s Combined Score, True Positive Rate, and 1-False Po... by Rahul Biswas (14117086)

Detection rates applied to all datasets based on all descriptors. by Reem Khalil (10898163)

Comparative study of CFC inference. by Rahul Biswas (14117086)

Resting state functional MRI brain signatures of fast disease progression in amyotrophic lateral sclerosis: a retrospective study by Francesca Trojsi (707124)

“…ALS patients were classified <i>a posteriori</i> into FPs (<i>n</i> = 25) and SPs (<i>n</i> = 29) based on changes in Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised score from baseline to the 18-month assessment (ΔALSFRS-R), applying a k-means clustering algorithm. …”

Data_Sheet_1_A novel framework of MOPSO-GDM in recognition of Alzheimer's EEG-based functional network.PDF by Ruofan Wang (7235729)

“…While improving the classification accuracy of application algorithms, we aim to expand our understanding of the brain function of patients with neurological disorders through the analysis of brain networks.…”

Table_1_Deep Learning Provides Exceptional Accuracy to ECoG-Based Functional Language Mapping for Epilepsy Surgery.DOCX by Harish RaviPrakash (8801666)

“…However, ECoG-FM has a low success rate when compared to the ESM. In this study, we address this critical limitation by developing a new algorithm based on deep learning for ECoG-FM and thereby we achieve an accuracy comparable to ESM in identifying eloquent language cortex. …”

Data_Sheet_1_Effect of acupuncture on brain regions modulation of mild cognitive impairment: A meta-analysis of functional magnetic resonance imaging studies.docx by Shiqi Ma (4684582)

“…In recent years, advances in neuroimaging techniques have provided new perspectives to elucidate the central mechanisms of acupuncture for MCI. Many acupuncture brain imaging studies have found significant improvements in brain function after acupuncture treatment of MCI, but the underlying mechanisms of brain regions modulation are unclear.…”

Image_1_Advancing the early detection of canine cognitive dysfunction syndrome with machine learning-enhanced blood-based biomarkers.TIF by Chae Young Kim (12433668)

Image_2_Advancing the early detection of canine cognitive dysfunction syndrome with machine learning-enhanced blood-based biomarkers.TIF by Chae Young Kim (12433668)

Data_Sheet_1_Advancing the early detection of canine cognitive dysfunction syndrome with machine learning-enhanced blood-based biomarkers.pdf by Chae Young Kim (12433668)

Data_Sheet_1_Using support vector machine to explore the difference of function connection between deficit and non-deficit schizophrenia based on gray matter volume.docx by Wenjing Zhu (487218)

“…This study aimed to investigate the alterations of functional connectivity between DS and NDS based on the ROI obtained by machine learning algorithms and differential GMV. …”

Table_1_A Phenotyping of Diastolic Function by Machine Learning Improves Prediction of Clinical Outcomes in Heart Failure.DOCX by Haruka Kameshima (11870333)

“…We tested the hypothesis that an unsupervised machine learning algorithm would detect heterogeneity in diastolic function and improve risk stratification compared with recommended consensus criteria.…”

Hardware_code. by Mehdi Nadiri Andabili (22097275)

“…The main goal of this field is to explore neural functionality in the brain. The studies of spiking neurons and Spiking Neural Networks (SNNs) are vital to understand how brain-inspired neural system work. …”

Software_code. by Mehdi Nadiri Andabili (22097275)

“…The main goal of this field is to explore neural functionality in the brain. The studies of spiking neurons and Spiking Neural Networks (SNNs) are vital to understand how brain-inspired neural system work. …”