EmbedTAD Using Graph Embedding and Unsupervised Learning to Identify TADs from High-Resolution Hi-C Data. [PDF]
Chowdhury HMAM, Oluwadare O.
europepmc +1 more source
A Metabolomic Signature Predicts Gout Flare Clinical Outcome Associated With Colchicine Prophylaxis
Objective This study investigated that serum metabolomics, before urate‐lowering therapy (ULT) initiation, could serve as a biomarker for responsiveness to colchicine prophylaxis in patients with gout commencing treat‐to‐target ULT. Methods We studied a multicenter prospective cohort (n = 409) initiating treat‐to‐target ULT plus colchicine prophylaxis.
Wenyan Sun +13 more
wiley +1 more source
Riemannian Manifolds for Biological Imaging Applications Based on Unsupervised Learning. [PDF]
Larin I, Karabelsky A.
europepmc +1 more source
Abstract Context‐centric proactive information delivery (PID) is a relatively underexplored domain within recommender systems (RS) aimed at enhancing Knowledge Workers' productivity by proactively providing relevant information during digital tasks.
Mahta Bakhshizadeh +4 more
wiley +1 more source
Unsupervised learning reveals landscape of local structural motifs across protein classes. [PDF]
Derry A +3 more
europepmc +1 more source
Tumor detection on bronchoscopic images by unsupervised learning. [PDF]
Liu Q, Zheng H, Jia Z, Shi Z.
europepmc +1 more source
GLP‐1 agonists and the gut microbiome: A bidirectional relationship
Abstract Glucagon‐like peptide‐1 (GLP‐1) receptor agonists have transformed the management of type 2 diabetes mellitus (T2DM) and obesity, yet their interactions with the gut microbiome remain an emerging frontier in pharmacological and metabolic research.
Srinivas Kamath +2 more
wiley +1 more source
Unsupervised Learning-Derived Complex Metabolic Signatures Refine Cardiometabolic Risk. [PDF]
Zhou Y +5 more
europepmc +1 more source
Transfer Learning Approaches in Bioprocess Engineering: Opportunities and Challenges
ABSTRACT Transfer learning (TL) has recently emerged as a promising approach to overcoming one of the key limitations of bioprocess engineering: data scarcity. By leveraging knowledge from one bioprocess to another, TL allows existing models and data sets to be reused efficiently, accelerating process development, improving prediction accuracy, and ...
Daniel Barón Díaz +3 more
wiley +1 more source
A data augmentation model integrating supervised and unsupervised learning for recommendation. [PDF]
Chen J +5 more
europepmc +1 more source

