Results 131 to 140 of about 66,762 (195)

Personalized sepsis mortality prediction: An interpretable machine learning nomogram. [PDF]

Clinics (Sao Paulo)
Weng L, Li H, Lv Y, Luo J, Wen Z, Shi J, Zhong L.   +6 more
europepmc   +1 more source

Predicting macrosomia and low birth weight with interpretable machine learning. [PDF]

BMC Pregnancy Childbirth
Cui M, Yang H, Wang B, Zhang J, Chu Q, Zhang C, Yao Z, Wang L.   +7 more
europepmc   +1 more source

A spatially interpretable machine learning framework for urban waterlogging risk mapping in Beijing. [PDF]

PeerJ
Tang Y.
europepmc   +1 more source

Deciphering Molecular and Solvent Effects on Aqueous and Organic Solubility through Interpretable Machine Learning Approaches. [PDF]

ACS Omega
Gopichand B, Nair GS, Nair BG, Melethadathil N.   +3 more
europepmc   +1 more source

Personalized risk prediction of financial toxicity in patients with cancer: an interpretable machine learning study. [PDF]

JNCI Cancer Spectr
Damgacioglu H, Sonawane K, Silvestri GA, Sterba KR, Hill EG, Cantor SB, Graboyes EM, Deshmukh AA.   +7 more
europepmc   +1 more source

Fast and Interpretable Machine Learning Modeling of Atmospheric Molecular Clusters. [PDF]

J Phys Chem A
Seppäläinen L, Kubečka J, Elm J, Puolamäki KR.   +3 more
europepmc   +1 more source

Interpretable Machine Learning for Predicting Splitting Strength of Asphalt Concrete: Insights from SHAP Analysis. [PDF]

Materials (Basel)
Xing J, Tan X, Li Y, Jin D, Guo P, Wang Y, Niu H.   +6 more
europepmc   +1 more source

Interpretable Machine Learning to Anticipate the Diagnostic Yield of EEG in the Emergency department. The EMINENCE study. [PDF]

J Med Syst
Scarpino M, Marra E, Liuzzi P, Piccardi B, Nazerian P, Sgrilli I, Mannini A, Nencioni A, Grippo A.   +8 more
europepmc   +1 more source

Interpretable machine learning to predict NOAF in ICU patients with CKD: validation in US and Chinese cohorts. [PDF]

Front Med (Lausanne)
Zhang S, Ren N, Yin Q, Yang C, Nie L, Zhao J, Liu Y, Huang J, Chen Y.   +8 more
europepmc   +1 more source

Interpretable machine learning for identifying adolescent obesity risk and identifying key determinants. [PDF]

Front Public Health
Huang L, Chen J.
europepmc   +1 more source