Patients improve, patterns persist: longitudinal stability of RA joint involvement patterns
Objective Rheumatoid arthritis is a heterogeneous disease. Data‐driven approaches, from synovial histology to joint involvement patterns (JIPs), have sought to define clinically meaningful subgroups. Whether these subgroups represent stable phenotypes or transient disease states remains unclear.
Tjardo Maarseveen +24 more
wiley +1 more source
Longitudinal non-negative matrix factorization identifies the altered trajectory of motor symptoms in Parkinson's disease. [PDF]
Hou X +8 more
europepmc +1 more source
Objective High body mass index (BMI ≥ 27 kg/m2) and aberrant gait biomechanics are primary risk factors for knee osteoarthritis (KOA), yet the specific loading patterns linked to clinical disease features remain unclear. Unsupervised machine learning (ML) was used to identify vertical ground reaction force (vGRF) waveform modes of variation and ...
Ashley N. Buck +10 more
wiley +1 more source
Nonnegative matrix factorization incorporating domain specific constraints for four dimensional scanning transmission electron microscopy. [PDF]
Kimoto K +7 more
europepmc +1 more source
Objective This study aimed to determine whether gout flare resolution is associated with physical activity and sleep. These findings were intended to inform the future development of a definition for flare resolution. Methods Data from 81 participants with gout who experienced at least one flare during a six‐month prospective observational study were ...
Sarah Stewart +12 more
wiley +1 more source
Near-Field Source Localization in Nonuniform Noise: An Efficient Symmetric Matrix Factorization-Based Approach. [PDF]
Song W, He Z, Sun G, Feng S.
europepmc +1 more source
An optimal pairwise merge algorithm improves the quality and consistency of nonnegative matrix factorization. [PDF]
Guo Y, Holy TE.
europepmc +1 more source
Fluorescence microscopy through scattering media with robust matrix factorization. [PDF]
Gao Z +7 more
europepmc +1 more source
Multi-layer matrix factorization for cancer subtyping using full and partial multi-omics dataset. [PDF]
Ren Y, Ren F, Yang B.
europepmc +1 more source

