Results 41 to 50 of about 4,586 (136)

Prediction of Depression Relapse Using Machine Learning With Administrative Data: Balancing Complexity and Simplicity

Quality and Reliability Engineering International, EarlyView.
ABSTRACT Depression is a mental disorder with a high lifetime prevalence and one of the leading causes of disability worldwide. As many patients experience another depressive episode after being treated, predictive monitoring for the risk of relapse is essential for healthcare professionals to be able to follow up on patients and intervene early ...
Paulina von Stackelberg, Rob Goedhart, Leo C. E. Huberts, Joran Lokkerbol, Ş. İlker Birbil   +4 more
wiley   +1 more source

Sectoral Evolution and Structural Transformation in Djibouti: A Multivariate and Regularized Regression Analysis Toward Achieving SDG 9

Sustainable Development, EarlyView.
ABSTRACT Djibouti's economic evolution over the past two decades reveals a distinct dual structure: a steadily expanding service sector that anchors the economy and a volatile industrial sector driven by episodic, foreign‐financed infrastructure projects.
Sadik Aden Dirir
wiley   +1 more source

Machine Learning on Systematically Curated Data Reveals Key Determinants of Magnetic Hyperthermia Performance

Small, EarlyView.
This study presents a machine‐learning (ML) framework to predict the specific absorption rate (SAR) of superparamagnetic iron oxide nanoparticles (SPIONs) for magnetic hyperthermia. A curated dataset comprising 30 intrinsic and extrinsic features revealed strong nonlinear dependencies.
Edgar Régulo Vega‐Carrasco, Shaquib Rahman Ansari, Jiaxi Zhao, Yael del Carmen Suárez‐López, Per Larsson, Alexandra Teleki   +5 more
wiley   +1 more source

Artificial intelligence streamlines scientific discovery of drug–target interactions

British Journal of Pharmacology, EarlyView.
Abstract Drug discovery is a complicated process through which new therapeutics are identified to prevent and treat specific diseases. Identification of drug–target interactions (DTIs) stands as a pivotal aspect within the realm of drug discovery and development. The traditional process of drug discovery, especially identification of DTIs, is marked by
Yuxin Yang, Feixiong Cheng
wiley   +1 more source

A Systematic Review on Applications of Artificial Intelligence for Obesity Prevention

Obesity Reviews, EarlyView.
ABSTRACT This systematic review examines the applications of artificial intelligence (AI) in preventing obesity, addressing a critical public health issue that affects a substantial portion of the population. With obesity rates rising alarmingly, particularly in the United States, this review synthesizes findings from 46 studies published between 2008 ...
Atefehsadat Haghighathoseini, Shuo‐yu Lin, Ge Song, Ruopeng An, Hong Xue   +4 more
wiley   +1 more source

Forecasting Carbon Prices: A Literature Review

Journal of Forecasting, Volume 45, Issue 2, Page 496-529, March 2026.
ABSTRACT Carbon emissions trading is utilized by a growing number of states as a significant tool for addressing greenhouse gas emissions (GHG), global warming problem and the climate crisis. Accurate forecasting of carbon prices is essential for effective policy design and investment strategies in climate change mitigation.
Konstantinos Bisiotis, Dimitris Christopoulos, George Tzougas   +2 more
wiley   +1 more source

Best Practices for Developing Linear Models With Multiple Explanatory Variables

Advanced Genetics, Volume 7, Issue 1, March 2026.
ABSTRACT Linear models, including t‐test, ANOVA, regression, ANCOVA, and generalized linear models, are foundational tools in statistical analysis. For large datasets, such as those involving tens of thousands of genes and millions of records, numerous advanced methods have been developed to improve both computational efficiency and reliability.
Baidu Li, Xinhai Li
wiley   +1 more source

Regression on manifolds: Estimation of the exterior derivative

, 2010
Collinearity and near-collinearity of predictors cause difficulties when doing regression. In these cases, variable selection becomes untenable because of mathematical issues concerning the existence and numerical stability of the regression coefficients,
Aswani, Anil, Bickel, Peter, Tomlin, Claire   +2 more
core   +2 more sources

BiGraph‐DTA: Predicting drug–target interactions of hepatoprotective agents with graph convolutional networks

Quantitative Biology, Volume 14, Issue 1, March 2026.
Abstract Predicting drug–target affinity (DTA) is critical for discovering and developing hepatoprotective agents that can prevent and treat liver diseases. In this study, we propose BiGraph‐DTA, a new predictive model for identifying DTA score prediction for hepatoprotective compounds by combining graph convolutional networks and bidirectional long ...
Arief Sartono, Bambang Riyanto Trilaksono, Sophi Damayanti, Anto Satriyo Nugroho, Firdayani Firdayani   +4 more
wiley   +1 more source

Integrative machine learning approach for identifying genes associated with quantitative traits: A soybean (Glycine max) yield case study

The Plant Genome, Volume 19, Issue 1, March 2026.
Abstract To improve the identification of minor‐effect molecular markers and genes associated with quantitative traits, addressing inefficiencies in traditional molecular marker mining and the limited impact of these markers in practical breeding, we analyzed over 15,000 soybean (Glycine max) genotypes across nine maturity groups using an AI‐driven ...
Wei Zhou, Haoyong Ouyang, Zhengxiao Yan, Jiayi Song, Yichan Li, Zhou Tang, Chang Zhao   +6 more
wiley   +1 more source