Results 251 to 260 of about 44,463 (307)

A machine learning-based online prediction model for recurrence risk in patients with <i>Klebsiella pneumoniae</i> liver abscess: a multicenter retrospective study. [PDF]

Front Cell Infect Microbiol
Zhang L, Wang Y, Dong Y, Qu Y, Fu Y, Chen J, Chen K, Cui J, Bai Z, Li J, Yu A.   +10 more
europepmc   +1 more source

Predicting Household Food Insecurity Through a Livelihood lens: A Machine Learning Approach in Rural Colombia

Journal of International Development, EarlyView.
ABSTRACT Food insecurity remains a persistent challenge in rural Colombia, driven by structural inequalities, livelihood constraints and exposure to shocks. This paper examined the determinants and predictive drivers of household food insecurity using nationally representative data from the Food and Agriculture Organisation (FAO) Data in Emergencies ...
Adrino Mazenda
wiley   +1 more source

Time-updated explainable machine learning predicts short-term mortality in peritoneal dialysis patients. [PDF]

Ren Fail
Wang Q, Ding Y, Luo Q, Wan S, Zhang Y.
europepmc   +1 more source

Early prediction of acute kidney injury in traumatic and non‐traumatic rhabdomyolysis using an interpretable machine learning model: A multicenter study with external validation

Journal of Intelligent Medicine, EarlyView.
Abstract Acute kidney injury (AKI) is a common and severe complication of rhabdomyolysis (RM), and early risk stratification remains challenging because of its multifactorial and heterogeneous nature. We developed and externally validated an interpretable machine learning (ML) model for early prediction of AKI in RM across traumatic and non‐traumatic ...
Chunli Liu, Jie Shi, Fengjuan Wang, Liang Ma, Huangang Hu, Li Zhang, Jie Song, Heng Jin, Dingwei Yang, Xiaoqin Guo, Haojun Fan, Qi Lv   +11 more
wiley   +1 more source

Interpretable machine learning to predict functional visual outcomes after the anti-VEGF loading phase for macular edema secondary to retinal vein occlusion: model development and temporal internal validation. [PDF]

Front Med (Lausanne)
Yu H, Teng J, Yao Z, Zhang Q, Liu T, Tao L.   +5 more
europepmc   +1 more source

Decadal Changes of UV Aerosol Optical Depth in Hobart, Australia Measured With a Brewer MKIII: Relationship to Bushfire Events and Climate Indices

International Journal of Climatology, EarlyView.
Monthly average aerosol optical depth at 320 nm obtained with a Brewer MKIII spectrophotometer for Hobart, Australia (42.8806° S, 147.3250° E) over a 21‐year period. There is a linear trend of 15.4% per decade. There are 9 months when the average aerosol optical depth exceeds twice the monthly standard deviation.
Manuel Nuñez, Antonio Serrano, Peter Love, Nels Larson   +3 more
wiley   +1 more source

Non-invasive prediction of detrusor underactivity in benign prostatic hyperplasia: an interpretable machine learning framework to optimize surgical selection. [PDF]

Front Med (Lausanne)
Gao L, Luo Z, Yuan Y, Luo Z, Zhuang H, Gao J, Xie X.   +6 more
europepmc   +1 more source

AI‐Driven Risk Governance for SMEs: From Predictive Analytics to Strategic Competitiveness

Strategic Change, EarlyView.
ABSTRACT Small and medium‐sized enterprises (SMEs) remain highly exposed to financial distress due to limited resources, volatile markets, and governance constraints. Traditional risk management often lacks a strategic and anticipatory orientation, highlighting the need for risk governance frameworks that integrate forecasting and adaptability.
Davide Liberato lo Conte, Giuseppe Sancetta, Nicola Cucari, Octavio Escobar   +3 more
wiley   +1 more source

Machine learning and metabolic modeling-based identification of hypoxia-driven metabolic signatures in pediatric cancers. [PDF]

Front Pharmacol
Sridhar S, Suraishkumar GK.
europepmc   +1 more source