Results 201 to 210 of about 1,171,833 (351)

A Novel Deep Temporal Feature Enhanced Just‐in‐Time Learning Framework for Predicting Rare Earth Component Content

Asia-Pacific Journal of Chemical Engineering, EarlyView.
ABSTRACT Real‐time online detection of rare earth element component contents is a crucial link in ensuring the stable production of the rare earth extraction and separation industry and improving the quality of rare earth products. The traditional methods for predicting the content of rare earth element components based on just‐in‐time learning fail to
Zhaohui Huang, Liangfang Liao, Chunfa Liao, Hui Zhang, Tao Qi, Rongxiu Lu, Wenhao Dai   +6 more
wiley   +1 more source

Can unsupervised machine learning gain new insights into urodynamic pressure flow pattern analysis? [PDF]

BJU Int
van Dort W, Rosier PFWM, van Steenbergen TRF, Geurts BJ, de Kort LMO.   +4 more
europepmc   +1 more source

Integrating One Health to Mitigate the Emergence and Spread of Antimicrobial Resistance in Livestock and Aquaculture

Animal Research and One Health, EarlyView.
Antimicrobial resistance (AMR) is an escalating global threat driven by antimicrobial use in aquaculture and livestock. Resistant pathogens and genes can spread across humans, animals, and the environment through interconnected ecosystems. Using a One Health approach, this review emphasizes antimicrobial stewardship, regulatory strengthening, enhanced ...
Mir Mohammad Ali, Delower Hossain, Ridwan Olamilekan Adesola, Anum Hanif, Shamsaldeen Ibrahim Saeed, Muhammad Abdul Mannan, Anoar Jamai Masroure, Kazi Estieque Alam, Md Kamal Hossain, Sabiha Zarin Tasnim Bristi, Md Jisan Ahmed   +10 more
wiley   +1 more source

Multi-Omics Analysis of Morbid Obesity Using a Patented Unsupervised Machine Learning Platform: Genomic, Biochemical, and Glycan Insights. [PDF]

Int J Mol Sci
Šnajdar I, Bulić L, Skelin A, Mršić L, Sokač M, Brkljačić M, Matovinović M, Linarić M, Kovačić J, Brlek P, Lauc G, Smolić M, Primorac D.   +12 more
europepmc   +1 more source

Unsupervised Machine-Learning Applications in Seismology

Catalogs of seismic source parameters (hypocenter locations, origin times, and magnitudes) are vital for studying various Earth processes, greatly enhancing our understanding of the nature of seismic events, the structure of the Earth, and the dynamics of fault systems.
openaire   +2 more sources

Molecular Stratification of Antiphospholipid Syndrome Through Integrative Analysis of the Whole‐Blood RNA Transcriptome

Arthritis &Rheumatology, EarlyView.
Objective Antiphospholipid syndrome (APS) is a thromboinflammatory disorder characterized by clinical and mechanistic heterogeneity that complicates early diagnosis and hinders targeted treatment. We aimed to identify distinct molecular endotypes among antiphospholipid antibody (aPL)–positive patients using whole‐blood transcriptomics.
Amala Ambati, Feiyang Ma, Katarina Kmetova, Sherwin Navaz, Claire K. Hoy, Cyrus Sarosh, Ajay Tambralli, Erika Navarro‐Mendoza, Johann E. Gudjonsson, J. Michelle Kahlenberg, Jacqueline A. Madison, Alí Duarte‐García, Jason S. Knight, Yu Zuo   +13 more
wiley   +1 more source

Anticoagulation management in intracerebral hemorrhage patients with deep vein thrombosis: insights from unsupervised machine learning and nomogram analysis. [PDF]

Front Neurol
Cui C, Yin Q, Long T, Guan H, Lao Z.
europepmc   +1 more source

A Metabolomic Signature Predicts Gout Flare Clinical Outcome Associated With Colchicine Prophylaxis

Arthritis &Rheumatology, EarlyView.
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, Lingfang Xu, Haibing Chen, Mingshu Sun, Zhiqiang Li, Rui Li, Lidan Ma, Hui Zhang, Aichang Ji, Yuwei He, Na Wu, Le Yan, Robert Terkeltaub, Changgui Li   +13 more
wiley   +1 more source

The value of unsupervised machine learning algorithms based on CT and MRI for predicting sarcopenia. [PDF]

Front Public Health
Zuo H, Bi Q, Liu X, Bi G, Wang Y, Wu Y, Yang G, Zhang C, Song Y, Wang G, Wang Q, Gong X.   +11 more
europepmc   +1 more source

Unsupervised machine learning analysis to enhance risk stratification in patients with asymptomatic aortic stenosis. [PDF]

Eur Heart J Digit Health
Fleury MA, Ohl L, Tastet L, Leclercq M, Precioso F, Mattei PA, Capoulade R, Abdoun K, Bédard É, Arsenault M, Beaudoin J, Bernier M, Salaun E, Bernard J, Shen M, Hecht S, Côté N, Droit A, Pibarot P.   +18 more
europepmc   +1 more source