Results 61 to 70 of about 329 (139)

st‐DenseViT: A Weakly Supervised Spatiotemporal Vision Transformer for Dense Prediction of Dynamic Brain Networks

Human Brain Mapping, Volume 46, Issue 14, 01 October 2025.
Overview of the proposed spatiotemporal dense prediction framework. The model takes 4D fMRI data as input and generates dynamic brain maps that evolve over time. The input is first patchified into a sequence of spatiotemporal tokens. A Vision Transformer (ViT) encoder is used to model complex spatial and temporal dependencies across these tokens.
Behnam Kazemivash, Pranav Suresh, Dong Hye Ye, Armin Iraji, Jingyu Liu, Sergey Plis, Peter Kochunov, David C. Zhu, Vince D. Calhoun   +8 more
wiley   +1 more source

Neuromarker Levels Also Predict Mortality in Adult Tuberculous Meningitis [PDF]

Clinical Infectious Diseases, 2018
Contains fulltext : 196415.pdf (Publisher’s version ) (Open Access)
van Laarhoven, A., Koeken, V., Dian, S., Ganiem, A.R, van Crevel, R., van Crevel, R.   +5 more
openaire   +3 more sources

Survey of Otolaryngologists on Delayed Epistaxis Following Posterior Nasal Nerve Ablation

International Forum of Allergy &Rhinology, Volume 16, Issue 10, Page 1235-1237, October 2026.
Jacob Schwartz, Carter Smith, Jose Luis Mattos   +2 more
wiley   +1 more source

Neuroimaging Data Informed Mood and Psychosis Diagnosis Using an Ensemble Deep Multimodal Framework

Human Brain Mapping, Volume 46, Issue 13, September 2025.
Combining fMRI and structural MRI with deep learning and ensemble methods, we refine psychiatric diagnosis by integrating neuroimaging with symptom‐based categories. Our findings highlight biologically homogeneous groups, identify potential biomarkers, and mitigate label noise, demonstrating that multimodal frameworks and ensemble models enhance ...
Hooman Rokham, Haleh Falakshahi, Godfrey D. Pearlson, Vince D. Calhoun   +3 more
wiley   +1 more source

NeuroMark SPECT Template

This contains the links to the text and NIFTI files of the NeuroMark SPECT template (version 1.0), with the 68 component ordered files. We have also included links to the TReNDS Github for easy access below: To view the original link to the TReNDS Center page, visit here: https://trendscenter.org/data/#WholeBrainSPECT202604 Github links to the ...
Harikumar, Amritha, Baker, Bradley, Amen, Daniel, Keator, David, Calhoun, Vince   +4 more
openaire   +2 more sources

Neurobiology-based cognitive biotypes using multi-scale intrinsic connectivity networks in psychotic disorders

Schizophrenia
Understanding neurobiology and developing effective interventions for cognitive dysfunction in psychotic disorders remain elusive. Insufficient knowledge about the biological heterogeneity of cognitive dysfunction hinders progress.
Pablo Andrés-Camazón, Covadonga M. Diaz-Caneja, Ram Ballem, Jiayu Chen, Vince D. Calhoun, Armin Iraji   +5 more
doaj   +1 more source

Multimodal neuromarkers in schizophrenia via cognition-guided MRI fusion [PDF]

Nature Communications, 2018
AbstractCognitive impairment is a feature of many psychiatric diseases, including schizophrenia. Here we aim to identify multimodal biomarkers for quantifying and predicting cognitive performance in individuals with schizophrenia and healthy controls. A supervised learning strategy is used to guide three-way multimodal magnetic resonance imaging (MRI ...
Jing Sui, Shile Qi, Theo G. M. van Erp, Juan Bustillo, Rongtao Jiang, Dongdong Lin, Jessica A. Turner, Eswar Damaraju, Andrew R. Mayer, Yue Cui, Zening Fu, Yuhui Du, Jiayu Chen, Steven G. Potkin, Adrian Preda, Daniel H. Mathalon, Judith M. Ford, James Voyvodic, Bryon A. Mueller, Aysenil Belger, Sarah C. McEwen, Daniel S. O’Leary, Agnes McMahon, Tianzi Jiang, Vince D. Calhoun   +24 more
openaire   +7 more sources

Altered Brain‐Behavior Association During Resting State is a Potential Psychosis Risk Marker

Advanced Science, Volume 12, Issue 26, July 10, 2025.
The study detects a potential multimodal biomarker that can be promising for identifying early markers of psychosis. It shows a consistent brain‐behavior association between a circuit of interconnected regions and executive function in neurotypical controls and individuals at various stages of psychosis.
Leonardo Fazio, Giuseppe Stolfa, Roberta Passiatore, Angelantonio Tavella, Giuseppe Blasi, Madalina O. Buciuman, Aaron L. Goldman, Shalaila S. Haas, Lana Kambeitz‐Ilankovic, Nikolaos Koutsouleris, Monica Nicoli, Teresa Popolizio, Antonio Rampino, Anne Ruef, Fabio Sambataro, Pierluigi Selvaggi, William Ulrich, Daniel R. Weinberger, Apulian Network on Risk for Psychosis, PRONIA Consortium, Alessandro Bertolino, Linda A. Antonucci, Giulio Pergola   +22 more
wiley   +1 more source

Complications of Novel Radiofrequency Device Use in Rhinology: A MAUDE Analysis [PDF]

With the widespread adoption of intranasal radiofrequency (RF) devices, our objective was to report national adverse events (AEs) associated with their use.
Nguyen, Theodore V, Kuan, Edward C, Bitner, Benjamin F, Wong, Brian JF, Torabi, Sina J, Abello, Eric H   +5 more
core   +1 more source

Towards Clinical Diagnoses: Classifying Alzheimer's Disease Using Single fMRI, Small Datasets, and Transfer Learning

Brain and Behavior, Volume 15, Issue 3, March 2025.
An outline of our transfer learning pipeline that is initially trained on an autism spectrum disorder (ASD) dataset and then fine‐tuned to an Alzheimer's disease (AD) classification task. Abstract Purpose Deep learning and functional magnetic resonance imaging (fMRI) are two unique methodologies that can be combined to diagnose Alzheimer's disease (AD).
Samuel L. Warren, Ahmed A. Moustafa, for the Alzheimer's Disease Neuroimaging Initiative   +2 more
wiley   +1 more source