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Emergent Language Symbolic Autoencoder (ELSA) with Weak Supervision to Model Hierarchical Brain Networks

Autor: Latheef, Ammar Ahmed Pallikonda, Santamaria-Pang, Alberto, Jones, Craig K, Sair, Haris I

Brain networks display a hierarchical organization, a complexity that poses a challenge for existing deep learning models, often structured as flat classifiers, leading to difficulties in interpretability and the 'black box' issue. To bridge this gap

Externí odkaz: http://arxiv.org/abs/2404.10031

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Evidential Uncertainty Quantification: A Variance-Based Perspective

Autor: Duan, Ruxiao, Caffo, Brian, Bai, Harrison X., Sair, Haris I., Jones, Craig

Uncertainty quantification of deep neural networks has become an active field of research and plays a crucial role in various downstream tasks such as active learning. Recent advances in evidential deep learning shed light on the direct quantificatio

Externí odkaz: http://arxiv.org/abs/2311.11367

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Applications of Sequential Learning for Medical Image Classification

Autor: Naim, Sohaib, Caffo, Brian, Sair, Haris I, Jones, Craig K

Purpose: The aim of this work is to develop a neural network training framework for continual training of small amounts of medical imaging data and create heuristics to assess training in the absence of a hold-out validation or test set. Materials an

Externí odkaz: http://arxiv.org/abs/2309.14591

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Deep Labeling of fMRI Brain Networks

Autor: Latheef, Ammar Ahmed Pallikonda, Ghate, Sejal, Hui, Zhipeng, Santamaria-Pang, Alberto, Tarapov, Ivan, Sair, Haris I, Jones, Craig K

Resting State Networks (RSNs) of the brain extracted from Resting State functional Magnetic Resonance Imaging (RS-fMRI) are used in the pre-surgical planning to guide the neurosurgeon. This is difficult, though, as expert knowledge is required to lab

Externí odkaz: http://arxiv.org/abs/2305.03814

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Akademický článek

Ferulic acid restores mitochondrial dynamics and autophagy via AMPK signaling pathway in a palmitate-induced hepatocyte model of metabolic syndrome

Autor: Yitong Li, Weiyang Zhao, Ali Tahir Sair, Tong Li, Rui Hai Liu

Publikováno v: Scientific Reports, Vol 14, Iss 1, Pp 1-15 (2024)

Abstract Mitochondrial dysfunction, characterized by elevated oxidative stress, impaired energy balance, and dysregulated mitochondrial dynamics, is a hallmark of metabolic syndrome (MetS) and its comorbidities. Ferulic acid (FA), a principal phenoli

Externí odkaz: https://doaj.org/article/eeb53db1f3ec4de888ca34b9b0d2a71a

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Active Learning in Brain Tumor Segmentation with Uncertainty Sampling, Annotation Redundancy Restriction, and Data Initialization

Autor: Kim, Daniel D, Chandra, Rajat S, Peng, Jian, Wu, Jing, Feng, Xue, Atalay, Michael, Bettegowda, Chetan, Jones, Craig, Sair, Haris, Liao, Wei-hua, Zhu, Chengzhang, Zou, Beiji, Yang, Li, Kazerooni, Anahita Fathi, Nabavizadeh, Ali, Bai, Harrison X, Jiao, Zhicheng

Deep learning models have demonstrated great potential in medical 3D imaging, but their development is limited by the expensive, large volume of annotated data required. Active learning (AL) addresses this by training a model on a subset of the most

Externí odkaz: http://arxiv.org/abs/2302.10185

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Deep Labeling of fMRI Brain Networks Using Cloud Based Processing

Autor: Ghate, Sejal, Santamaria-Pang, Alberto, Tarapov, Ivan, Sair, Haris I, Jones, Craig K

Resting state fMRI is an imaging modality which reveals brain activity localization through signal changes, in what is known as Resting State Networks (RSNs). This technique is gaining popularity in neurosurgical pre-planning to visualize the functio

Externí odkaz: http://arxiv.org/abs/2209.08200

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