Kenneth S Kosik
Kenneth S Kosik
Rapid advances in human brain organoid technologies have prompted the question of their consciousness. Although brain organoids resemble many facets of the brain, their shortcomings strongly suggest that they do not fit any of the operation...
CellContrast: Reconstructing spatial relationships in single-cell RNA sequencing data via deep contrastive learning [0.03%]
基于深度对比学习的单细胞RNA测序数据的空间关系重建（CellContrast）
Shumin Li,Jiajun Ma,Tianyi Zhao et al.
Shumin Li et al.
A vast amount of single-cell RNA sequencing (SC) data have been accumulated via various studies and consortiums, but the lack of spatial information limits its analysis of complex biological activities. To bridge this gap, we introduce Cell...
A federated learning architecture for secure and private neuroimaging analysis [0.03%]
一种安全且私密的神经影像分析联邦学习架构
Dimitris Stripelis,Umang Gupta,Hamza Saleem et al.
Dimitris Stripelis et al.
The amount of biomedical data continues to grow rapidly. However, collecting data from multiple sites for joint analysis remains challenging due to security, privacy, and regulatory concerns. To overcome this challenge, we use federated lea...
psHarmonize: Facilitating reproducible large-scale pre-statistical data harmonization and documentation in R [0.03%]
基于R的可重复的大规模预统计数据统一和文档化工具包psHarmonize
John J Stephen,Padraig Carolan,Amy E Krefman et al.
John J Stephen et al.
Combining pertinent data from multiple studies can increase the robustness of epidemiological investigations. Effective "pre-statistical" data harmonization is paramount to the streamlined conduct of collective, multi-study analysis. Harmon...
Reliable imputation of spatial transcriptomes with uncertainty estimation and spatial regularization [0.03%]
具有不确定性估计和空间正则化的可靠的空间转录组插补方法
Chen Qiao,Yuanhua Huang
Chen Qiao
Imputation of missing features in spatial transcriptomics is urgently needed due to technological limitations. However, most existing computational methods suffer from moderate accuracy and cannot estimate the reliability of the imputation....
Kang Zhang,Hong-Yu Zhou,Daniel T Baptista-Hon et al.
Kang Zhang et al.
The digital twin (DT) is a concept widely used in industry to create digital replicas of physical objects or systems. The dynamic, bi-directional link between the physical entity and its digital counterpart enables a real-time update of the...
A hierarchically annotated dataset drives tangled filament recognition in digital neuron reconstruction [0.03%]
一个分层注释的数据集推动了数字神经元重建中缠绕纤丝的识别
Wu Chen,Mingwei Liao,Shengda Bao et al.
Wu Chen et al.
Reconstructing neuronal morphology is vital for classifying neurons and mapping brain connectivity. However, it remains a significant challenge due to its complex structure, dense distribution, and low image contrast. In particular, AI-assi...
ProLesA-Net: A multi-channel 3D architecture for prostate MRI lesion segmentation with multi-scale channel and spatial attentions [0.03%]
具有多尺度通道和空间注意力的前列腺MRI病变分割的多通道3D ProLesA-Net网络架构
Dimitrios I Zaridis,Eugenia Mylona,Nikos Tsiknakis et al.
Dimitrios I Zaridis et al.
Prostate cancer diagnosis and treatment relies on precise MRI lesion segmentation, a challenge notably for small (
Guang Yang,Brandon Edwards,Spyridon Bakas et al.
Guang Yang et al.
Federated learning for privacy-preserving depression detection with multilingual language models in social media posts [0.03%]
基于社交媒体帖子的多语言模型的联合学习隐私保护抑郁症检测方法
Samar Samir Khalil,Noha S Tawfik,Marco Spruit
Samar Samir Khalil
The incidences of mental health illnesses, such as suicidal ideation and depression, are increasing, which highlights the urgent need for early detection methods. There is a growing interest in using natural language processing (NLP) models...