Results 141 to 150 of about 29,456 (261)

Machine learning and SHAP value interpretation for predicting cardiovascular disease risk in patients with diabetes using dietary antioxidants. [PDF]

Front Nutr
Zhang X, Lin S, Zeng Q, Peng L, Yan C.
europepmc   +1 more source

Accelerating Materials Discovery: A Review of Machine Learning in X‐Ray Absorption Spectroscopy

Advanced Intelligent Systems, EarlyView.
This review systematically details how machine learning transforms X‐ray absorption spectroscopy (XAS) analysis. It covers advanced deep learning architectures for structure‐spectra mapping and inverse tasks, while discussing key challenges like the simulation‐to‐reality gap.
Melaku Lake Tegegne, Haodong Yao, Liyuan Wu, Yihe Pang, Fazhi Qi, Lina Zhao   +5 more
wiley   +1 more source

Prediction of prolonged length of stay from first 2 days of hospitalization data: a SHAP value-based variable selection method for a simplified model. [PDF]

Int J Qual Health Care
Fa R, Stoessel D, Artemova S, von Schenck U, Nowparast Rostami H, Madiot PE, Landelle C, Bosson JL.   +7 more
europepmc   +1 more source

Integration of Liquid Handling Robotics, Turbidimetry, and Machine Learning Toward Inverse Design of Lower Critical Solution Temperature Polymer Formulations

Advanced Intelligent Systems, EarlyView.
An integrated OT‐2/plate reader platform automates LCST cloud point measurement of NIPAM‐co‐DMAEMA copolymers across high‐dimensional formulation spaces. Machine learning trained on the resulting high‐throughput datasets achieves R2 up to 0.96 and enables inverse design of polymer formulations to target transition temperatures with <1% error.
Lachlan Alexander, Vianna F. Jafari, Tanja Junkers   +2 more
wiley   +1 more source

Machine learning based predictive model of the risk of Tourette syndrome with SHAP value interpretation: a retrospective observational study. [PDF]

Sci Rep
Li A, Liu Y, Luo Y, Xiao X, Xiao W, Xie R, Deng X, Chen Z, Zhou Q, Gong Y, Chen Z, Xu H.   +11 more
europepmc   +1 more source

Responsible Artificial Intelligence in Courts: A Four‐Test Framework

AI &Innovation, EarlyView.
ABSTRACT A structured framework for responsible AI applications relating to judicial decision‐making and the adjudicative functions of courts requires the satisfaction of multiple context‐specific safeguards. This article proposes a four‐test framework designed to evaluate whether AI systems used in courts operate in accordance with legal, procedural ...
Kwan Yiu Cheng
wiley   +1 more source

Machine learning and SHAP value interpretation for predicting the response to neoadjuvant chemotherapy and long-term clinical outcomes in Chinese female breast cancer. [PDF]

Ann Med
Yuan Q, Ye R, Qian Y, Yu H, Zhou Y, Cui X, Liu F, Niu M.   +7 more
europepmc   +1 more source

Proteomic Profiling of Nodal T‐Follicular Helper Cell Lymphoma Reveals Distinct Biological Signatures and Improves Prognostic Stratification Beyond the IPI

American Journal of Hematology, EarlyView.
ABSTRACT Nodal T‐follicular helper cell lymphoma (nTFHL), most commonly of angioimmunoblastic type, exhibits heterogeneous clinical outcomes that are not fully explained by current clinical and biological variables. While genetic alterations have been extensively investigated, its proteomic landscape remains largely unexplored.
David Beauvais, Yanis Zirem, Tristan Cardon, Soulaimane Aboulouard, Romain Dubois, Isabelle Fournier, Franck Morschhauser, Michel Salzet, Ibrahim Yakoub‐Agha, Marie Duhamel   +9 more
wiley   +1 more source

Machine learning and SHAP value interpretation for predicting comorbidity of cardiovascular disease and cancer with dietary antioxidants. [PDF]

Redox Biol
Qi X, Wang S, Fang C, Jia J, Lin L, Yuan T.   +5 more
europepmc   +1 more source

Advancing Environmental Sustainability: The Role of Artificial Intelligence in Monitoring, Predicting, and Controlling Sulfur Dioxide Emissions

Asia-Pacific Journal of Chemical Engineering, EarlyView.
ABSTRACT Air pollution from sulfur dioxide (SO2) emissions poses significant threats to environmental sustainability, public health, and climate change efforts. Despite advances in monitoring and regulatory frameworks, traditional methods often fall short in accuracy, scalability, and efficiency.
Turkan Kopac
wiley   +1 more source