Sarthak Pati
Sarthak Pati
Fragmented AI tools struggle with the complex diagnosis of fine-grained diseases from radiological images. A new study in Patterns introduces the "screening-to-subtyping" (S2S) framework, a holistic deep learning system integrating the enti...
Christopher Wood,Hao Wang,Wei-Jun Yang et al.
Christopher Wood et al.
Human brain organoids (HBOs) have emerged as transformative models for neurodevelopment and disease, yet ethical concerns persist regarding their potential to develop consciousness. Since 2020, a growing cohort of neuroscientists and philos...
Generating and leveraging explanations of AI/ML models in materials and manufacturing research [0.03%]
生成和利用AI / ML模型在材料和制造研究中的解释能力
Erick J Braham,Jennifer M Ruddock,James O Hardin
Erick J Braham
In some technical domains, machine learning (ML) tools, typically used with large datasets, must be adapted to small datasets, opaque design spaces, and expensive data generation. Specifically, generating data in many materials or manufactu...
Edith Luhanga
Edith Luhanga
Edith Luhanga is an assistant research professor at Carnegie Mellon University Africa in Rwanda. Her work focuses on designing and evaluating technologies that leverage artificial intelligence (AI) to promote behavioral change in low-resour...
Pinar Alper,Flora D&#x;Anna,Bert Droesbeke et al.
Pinar Alper et al.
The rise of data-driven scientific investigations has made research data management (RDM) essential for good scientific practice. Implementing RDM is a complex challenge for research communities, infrastructures, and host organizations. Gen...
A novel quantum algorithm for efficient attractor search in gene regulatory networks [0.03%]
一种在基因调控网络中高效寻找平衡点的量子算法
Mirko Rossini,Felix M Weidner,Joachim Ankerhold et al.
Mirko Rossini et al.
Describing gene interactions in cells is challenging due to their complexity and the limited microscopic detail available. Boolean networks offer a powerful, coarse-grained approach to modeling these dynamics using binary agents and their i...
cytoGPNet: Enhancing clinical outcome prediction accuracy using longitudinal cytometry data in small cohort studies [0.03%]
基于小样本队列纵向细胞学数据的临床结果预测方法的研究
Jingxuan Zhang,Liwen Sun,Neal E Ready et al.
Jingxuan Zhang et al.
Cytometry data, including flow and mass cytometry, are widely used in immunological studies such as cancer immunotherapy and vaccine trials. These data provide rich insights into immune cell dynamics and their relationship to clinical outco...
A one-shot, lossless algorithm for cross-cohort learning in mixed-outcomes analysis [0.03%]
一种一次性、无损算法在混合结果分析中跨队列学习中的应用
Ruowang Li,Luke Benz,Rui Duan et al.
Ruowang Li et al.
In cross-cohort studies, integrating diverse datasets is essential and challenging due to cohort-specific variations, distributed data storage, and privacy concerns. Traditional methods often require data pooling or harmonization, which can...
Global understanding via local extraction for data clustering and visualization [0.03%]
基于局部提取的全局理解在数据聚类与可视化中的应用研究
Zhenyue Zhang,Bingjie Li
Zhenyue Zhang
Retrieving latent class patterns from complex data is challenging. This paper focuses on the problem of retrieving latent classes from local connections of raw data without any assumptions regarding data structures or distributions. We prop...
Achieving handle-level random access in an encrypted DNA archival storage system via frequency dictionary mapping coding [0.03%]
基于频率词典映射编码的加密DNA存档存储系统中实现随机访问
Ben Cao,Xue Li,Bin Wang et al.
Ben Cao et al.
DNA storage provides a high storage density and durability, but current systems experience high latency and lack data security. This study proposed the use of frequency dictionary mapping coding (FDMC) to enable handle-level random access o...