6 results found

Arman Ghavidel, Pilar Pazos, Hyoshin J. Park, John Seems

Prostate cancer risk prediction remains challenged by the inability to reliably distinguish indolent from aggressive disease, leading to overtreatment or undertreatment. Conventional approaches based ...

Research Square 2026-04-23 rs-9490581
Prostate cancer Risk stratification Longitudinal PSA/DRE Deep learning Outcome-guided clustering

NGIMBOG MBOGUE Joseph, KONLACK TALLA Belmien Carlos, VIDEME BOSSOU Olivier, TCHUIDJAN Roger

Device-to-device (D2D) communications play a key role in today's communication infrastructures. They help optimise network capacity, reduce latency and enhance quality of service. The main difficulty ...

Wireless Personal Communications 2026-04-23 rs-9032690
D2D; D2D communications 5G Clustering Cluster-head

Jingyun Zhu, Liu Liu, Kaixian Ren, Peiyan Zhu, Lang Bai, Minting Chen

Background Meibomian gland dysfunction (MGD) is the leading cause of evaporative dry eye and is characterized by gland obstruction, lipid imbalance, and tear film instability. While inflammatory mecha...

BMC Ophthalmology 2026-04-23 rs-9303325
meibum meibomian gland dysfunction (MGD) high-fidelity lipidomics lipid layer pattern cluster analysis Protein-Protein Interaction (PPI)

Grethel Garcia Bu Bucogen

Nocturnal cooling during frost events in complex terrain is governed by interactions between topography and boundary-layer processes, yet these dynamics remain poorly resolved at high temporal resolut...

Research Square 2026-04-22 rs-9484595
GOES-16 thermal remote sensing frost risk cold-air pooling clustering topographic controls

Surendiran Muthukumar, Deepalakshmi Kumar, Ranjit Panigrahi, Paolo Barsocchi, Akash Kumar Bhoi

Data heterogeneity remains one of the most significant challenges in federated learning (FL), impacting model performance, convergence, and scalability. This issue is especially critical in healthcare...

Journal of Big Data 2026-04-22 rs-8191856
Federated Learning Data Heterogeneity Clustering Personalized Models Healthcare Informatics Non-IID Data Privacy Preservation

Aaron Danielson

 Clustering is widely used to discover interpretable structure in data, but  conventional unsupervised methods group examples by \emph{feature similarity}  alone, ignoring any available prediction tar...

Research Square 2026-04-21 rs-9163443
supervised clustering prototype learning cross-attention interpretable machine learning tabular data regime discovery
Back to Top
Home
Browse
Submit
About
0.028424s