Results 231 to 240 of about 150,441 (331)

Explicit Features Versus Implicit Spatial Relations in Geomorphometry: A Comparative Analysis for DEM Error Correction in Complex Geomorphological Regions. [PDF]

Sensors (Basel)
Zhou S, Xie M, Ju N, Feng C, Lin Q, Shu Z.   +5 more
europepmc   +1 more source

Protective Effects of Riociguat Against Contrast‐Induced Nephropathy: An Experimental and Machine Learning‐Based Study in Rats

The Kaohsiung Journal of Medical Sciences, EarlyView.
ABSTRACT Contrast‐induced nephropathy (CIN) is an important cause of acute kidney injury following exposure to iodinated contrast media, and effective preventive strategies remain limited. This study investigated the renoprotective effects of riociguat, a soluble guanylate cyclase stimulator, in an experimental rat model of CIN and explored machine ...
Mustafa Begenc Tascanov, Kenan Toprak, Sibel Turedi, İsmail Koyuncu, Zulkif Tanrıverdi, Necip Fazıl Dedeoglu, Halil Fedai, Asuman Bicer, İbrahim Halil Altıparmak, Recep Demirbag, Gencay Sarıısık   +10 more
wiley   +1 more source

The role of anesthesia in TKA length of stay: a data-driven analysis using Boruta algorithm. [PDF]

Front Med (Lausanne)
Fan L, Liu J, Ma L, Ren J.
europepmc   +1 more source

Predictive Modelling of Solvent Effects on Drug Incorporation into Polymeric Nanocarriers: A Machine Learning Approach

Macromolecular Rapid Communications, EarlyView.
When seeking nanoparticles with elevated drug loading content, the experimental setup, including solvent selection, is crucial. Through machine learning, we pinpointed that the drug's solubility in the organic solvent is the key factor for attaining high drug loading content.
Wei Ge, Ramindu De Silva, Yanan Fan, Scott A. Sisson, Martina H. Stenzel   +4 more
wiley   +1 more source

Decoding the renal-cochlear axis: explainable machine learning and phenotype clustering reveal high-risk hearing loss subtypes in CKD. [PDF]

Ren Fail
Chen L, Wang J, Liu G, Zhao Y, Zhou Z, Li Q.   +5 more
europepmc   +1 more source

Optimized XGBoost modeling for accurate battery capacity degradation prediction

Results in Engineering
Sadiqa Jafari, Ji-Hyeok Yang, Y. Byun
semanticscholar   +1 more source

Role of High Fidelity Vs. Low Fidelity Experimental Data in Machine Learning Model Performance for Predicting Polymer Solubility

Macromolecular Rapid Communications, EarlyView.
The performance of machine learning models for classifying polymer solubility improves when a high‐fidelity experimental dataset is used compared to a low‐fidelity experimental dataset. This has important implications for justifying the value of spending additional time and resources preparing detailed experimental datasets.
Mona Amrihesari, Manali Banerjee, Raul Olmedo, Blair Brettmann   +3 more
wiley   +1 more source

Risk factors and a predictive model for steinstrasse formation after shock wave lithotripsy in pediatric urolithiasis. [PDF]

Urolithiasis
Çoban F, Kutlu H, Akbaba KT, Deniz ME, Kalyenci B.   +4 more
europepmc   +1 more source

Challenges and Opportunities in Machine Learning for Light‐Emitting Polymers

Macromolecular Rapid Communications, EarlyView.
The performance of light‐emitting polymers emerges from coupled effects of chemical diversity, morphology, and exciton dynamics across multiple length scales. This Perspective reviews recent design strategies and experimental challenges, and discusses how machine learning can unify descriptors, data, and modeling approaches to efficiently navigate ...
Tian Tian, Yinyin Bao
wiley   +1 more source