Results 91 to 100 of about 1,027 (170)

SlideMamba: entropy-based adaptive fusion of GNN and Mamba for enhanced representation learning in digital pathology. [PDF]

Sci Rep
Khan S, Dambandkhameneh F, Shaikh N, Nie Y, Venugopal R, Li X.   +5 more
europepmc   +1 more source

The role of artificial intelligence-based foundation models and "copilots" in cancer pathology: potential and challenges. [PDF]

J Exp Clin Cancer Res
Cheng CH, Wong CC.
europepmc   +1 more source

Machine-learning models based on histological images from healthy donors identify imageQTLs and predict chronological age. [PDF]

Proc Natl Acad Sci U S A
Meng R, Zhu W, Cameron CJF, Ni P, Zhou X, Ulammandakh T, Gerstein MB.   +6 more
europepmc   +1 more source

Plug-and-play computational method for advancing natural and biomedical image representation. [PDF]

Patterns (N Y)
Gong H, Han T, Li G.
europepmc   +1 more source

Self-supervised learning for data augmentation in histopathology image segmentation. [PDF]

Sci Rep
Almubarak HA.
europepmc   +1 more source

Robust Cell-Level Classification for Liquid-Based Cervical Cytology Using Deep Transfer Learning: A Multi-Source Study Addressing Scanner-Induced Domain Shifts. [PDF]

Bioengineering (Basel)
Coskun G, Akuner MC, Kaplanoglu E.
europepmc   +1 more source

Fusion Annotator: A Platform for Accelerating Consensus-Driven Ground Truth Generation with AI Assistance. [PDF]

Proc SPIE Int Soc Opt Eng
Kumar SKC, Afsari F, Lucarelli N, Srivastav D, Rosenberg AZ, Border S, Clapp W, Phillips C, Gupta A, Eadon MT, Strekalova YAL, Sarder P.   +11 more
europepmc   +1 more source

A computation-efficient network with feature aggregation for cancer subtype classification on histopathological images. [PDF]

Eng Appl Artif Intell
Fan Z, Zhang C, Sun L, Thorstad W, Gay H, Wang X, Li H.   +6 more
europepmc   +1 more source

Practical guidelines for multiple instance learning in computational pathology: how embedding choice impacts overall survival prediction. [PDF]

Front Bioinform
Miccolis F, Ficarra E, Lovino M.
europepmc   +1 more source

Editorial: Visualizing big culture and history data. [PDF]

Front Big Data
Windhager F, Koch S, Münster S, Mayr E.
europepmc   +1 more source