Machine Learning on Dynamic Functional Connectivity: Promise, Pitfalls, and Interpretations [0.03%]
基于动态功能连接的机器学习：前景、困境及其解释
Jiaqi Ding,Tingting Dan,Ziquan Wei et al.
Jiaqi Ding et al.
An unprecedented amount of existing functional Magnetic Resonance Imaging (fMRI) data provides a new opportunity to understand how functional fluctuations relate to human cognition/behavior using data-driven approaches. To this end, tremend...
A multimodal machine learning approach to predict Fugl-Meyer scores and motor recovery potential in stroke rehabilitation: Toward precision-based therapies [0.03%]
一种多模态机器学习方法预测卒中康复中的Fugl-Meyer评分和运动恢复潜力：基于精准疗法的研究
Laura Dipietro,Uri Eden,Paulo Teixeira et al.
Laura Dipietro et al.
Stroke is a leading cause of long-term disability, with highly variable recovery trajectories and challenges in prediction and monitoring. Frequently used measures (e.g., National Institute of Health Stroke Scale (NIHSS) and Fugl-Meyer (FM)...
Chong Peng,Zhilu Zhang,Chenglizhao Chen et al.
Chong Peng et al.
In this paper, we propose a new Semi-Nonnegative Matrix Factorization method for 2-dimensional (2D) data, named TS-NMF. It overcomes the drawback of existing methods that seriously damage the spatial information of the data by converting 2D...
Causality-aware Social Recommender System with Network Homophily Informed Multi-treatment Confounders [0.03%]
一种基于网络同构多治疗混淆变量的因果感知型社交推荐系统
Xin Zan,Alexander Semenov,Chao Wang et al.
Xin Zan et al.
Typical recommender systems utilize observed ratings of users as inputs to learn their preferences and aim to output recommendations of new items that users will like by predicting their potential ratings. The real world is driven by causal...
An optimal Bayesian intervention policy in response to unknown dynamic cell stimuli [0.03%]
应对未知动态细胞刺激的最优贝叶斯干预政策
Seyed Hamid Hosseini,Mahdi Imani
Seyed Hamid Hosseini
Interventions in gene regulatory networks (GRNs) aim to restore normal functions of cells experiencing abnormal behavior, such as uncontrolled cell proliferation. The dynamic, uncertain, and complex nature of cellular processes poses signif...
Amr Elsisy,Aamir Mandviwalla,Boleslaw K Szymanski et al.
Amr Elsisy et al.
We focus on organizational structures in covert networks, such as criminal or terrorist networks. Their members engage in illegal activities and attempt to hide their association and interactions with these networks. Hence, data about such ...
HRL4EC: Hierarchical reinforcement learning for multi-mode epidemic control [0.03%]
基于分层增强学习的多模式流行病控制方法
Xinqi Du,Hechang Chen,Bo Yang et al.
Xinqi Du et al.
Infectious diseases, such as Black Death, Spanish Flu, and COVID-19, have accompanied human history and threatened public health, resulting in enormous infections and even deaths among citizens. Because of their rapid development and huge i...
Modeling the spread dynamics of multiple-variant coronavirus disease under public health interventions: A general framework [0.03%]
公共卫生干预下的多种新型冠状病毒传播动力学建模：一种通用框架
Choujun Zhan,Yufan Zheng,Lujiao Shao et al.
Choujun Zhan et al.
The COVID-19 pandemic was caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is a single-stranded positive-stranded RNA virus with a high multi-directional mutation rate. Many new variants even have an immune-evad...
Deep features to detect pulmonary abnormalities in chest X-rays due to infectious diseaseX: Covid-19, pneumonia, and tuberculosis [0.03%]
用于检测胸部X光片中感染性疾病所致肺部异常的深度特征：COVID-19、肺炎和结核病
Md Kawsher Mahbub,Milon Biswas,Loveleen Gaur et al.
Md Kawsher Mahbub et al.
Chest X-ray (CXR) imaging is a low-cost, easy-to-use imaging alternative that can be used to diagnose/screen pulmonary abnormalities due to infectious diseaseX: Covid-19, Pneumonia and Tuberculosis (TB). Not limited to binary decisions (wit...
MIC-Net: A deep network for cross-site segmentation of COVID-19 infection in the fog-assisted IoMT [0.03%]
MIC-Net：雾辅助IoMT中COVID-19感染跨站点分割的深度网络
Weiping Ding,Mohamed Abdel-Basset,Hossam Hawash et al.
Weiping Ding et al.
The automatic segmentation of COVID-19 pneumonia from a computerized tomography (CT) scan has become a major interest for scholars in developing a powerful diagnostic framework in the Internet of Medical Things (IoMT). Federated deep learni...