Results 191 to 200 of about 934,428 (242)
FLARE, a multimodal AI framework, combines pathology slides, radiology scans, and clinical reports to predict colorectal cancer outcomes, even when some tests are missing. Evaluated retrospectively in 1679 patients from four medical centers, it consistently achieved the best prognostic accuracy and clearly separated high‐ and low‐risk groups.
Linhao Qu +6 more
wiley +1 more source
Uncertainty-weighted semi-supervised learning with dynamic entropy masking and Bhattacharyya-regularized loss. [PDF]
Ghazal MT, Tanha J, Shahi N, Roshan S.
europepmc +1 more source
The Disordered Region of ASXL1 Acts as an Auto‐Regulator Through Condensation
ASXL1's long IDR encodes an electrostatic “basic platform + acidic brake” that autoregulates condensation. Truncation at a clinical hotspot lifts this brake, forming condensates that retarget BRD2, remodel local chromatin accessibility, and impair neutrophil maturation.
Xiao Fang, Qiwei Li, Wenqing Zhang
wiley +1 more source
From pretraining to privacy: federated ultrasound foundation model with self-supervised learning. [PDF]
Jiang Y +17 more
europepmc +1 more source
Tumor evolution in lung adenocarcinoma is shaped by genetic alterations and spatial immune dynamics. By integrating whole‐exome sequencing, imaging mass cytometry, and spatial transcriptomics across two mouse models, this study reveals how mutational burden, immune infiltration, and cell–state interactions evolve during early and late carcinogenesis ...
Bo Zhu +34 more
wiley +1 more source
Mid‐infrared optoacoustic microscopy (MiROM) acquires lipid‐ and protein‐ associated vibrational contrast in intact fat tissue without dyes, preserving native tissue architecture. Through lateral and axial segmentation, MiROM tracks intrinsic intracellular changes during postnatal remodeling. A quantitative spatial analysis tool (Q‐SAT) maps white‐ and
Myeongseop Kim +7 more
wiley +1 more source
Supervised-Learning-Driven Interrogation of Organ-on-a-Chip Quality from Microscopy Images. [PDF]
George RM, Kenry.
europepmc +1 more source
MGM as a Large‐Scale Pretrained Foundation Model for Microbiome Analyses in Diverse Contexts
We present the Microbial General Model (MGM), a transformer‐based foundation model pretrained on over 260,000 microbiome samples. MGM learns contextualized microbial representations via self‐supervised language modeling, enabling robust transfer learning, cross‐regional generalization, keystone taxa discovery, and prompt‐guided generation of realistic,
Haohong Zhang +5 more
wiley +1 more source
Feedback Recorrection Semantic-Based Image Inpainting Under Semi-Supervised Learning. [PDF]
Ye X, Tan R, Sui M, Chen H, Ying N.
europepmc +1 more source
Learned Conformational Space and Pharmacophore Into Molecular Foundational Model
The Ouroboros model introduces two orthogonal modules within a unified framework that independently learn molecular representations and generate chemical structures. This design enables flexible optimization strategies for each module and faithful structure reconstruction without prompts or noise.
Lin Wang +8 more
wiley +1 more source

