Results 251 to 260 of about 302,402 (283)

Hierarchical Superposition Framework Reveals the Complex Effects of Natural Medicine Formulas

Advanced Intelligent Systems, EarlyView.
A novel hierarchical superposition pharmacological model incorporates the principle of hierarchical structures from physics to simulate the spatiotemporal dynamics of drug combinations, to elucidate the universal law underlying drug combination effects. By modeling cross‐level causal transmission and attenuation, it advances beyond traditional additive
Weifeng Liang, Dingsi Xiang, Shengli Mi, Jiajun Huang   +3 more
wiley   +1 more source

Leveraging Compressed Sensing and Radiomics for Robust Feature Selection for Outcome Prediction in Personalized Ultra‐Fractionated Stereotactic Adaptive Radiotherapy

Advanced Intelligent Systems, EarlyView.
A compressed sensing (CS)‐based feature selection method is proposed to select the most informative elements in the radiomic features extracted from medical images of personalized ultra‐fractionated stereotactic adaptive treatment. The CS‐based approach is able to simplify the feature selection process and enhance the accuracy and robustness of a ...
Yajun Yu, Steve Jiang, Robert Timmerman, Hao Peng   +3 more
wiley   +1 more source

Empowering Biomedical Research with Foundation Models in Computational Microscopy: A Systematic Review

Advanced Intelligent Systems, EarlyView.
The integration of foundation models into computational microscopy revolutionizes biomedical research by enhancing imaging resolution, accelerating data analysis, and enabling real‐time biological interpretation. This systematic review critically examines recent advancements, highlights translational challenges, and discusses the transformative ...
Di Ding, Tianliang Yao, Genyi Feng, Xueqing Gao, Xusen Sun, Rong Luo   +5 more
wiley   +1 more source

MO‐hHHO: Multi‐Objective Hybrid Harris Hawks Optimization for Prediction of Coronary Artery Disease

Advanced Intelligent Systems, EarlyView.
This article proposes a novel Multi‐Objective hybrid Harris Hawks Optimization (MO‐hHHO) algorithm for simultaneous feature selection and hyperparameter tuning in heart disease classification. The approach leverages adaptive exploration‐exploitation strategies to enhance convergence efficiency.
Anu Ragavi Vijayaraj, Subbulakshmi Pasupathi   +1 more
wiley   +1 more source

Clinlabomics‐Enabled Blending Ensemble Learning for Low‐Cost Pan‐Cancer Detection and Classification Using Routine Clinical Laboratory Data

Advanced Intelligent Systems, EarlyView.
Researchers develop clinlabomics assisted for cancer identification, an artificial intelligence‐powered system using routine clinical lab data to detect and identify 10 cancer types. Tested on 19 199 individuals, it achieves 90.39% sensitivity and 82.41% specificity in cancer detection, with 72.57% accuracy in identifying specific cancer types ...
Bowen Zhang, Lin Li, Long Cheng, Yujie Liu, Zhaoqing Liu, Jiangpeng Wu, Pengyi Zhang, Jiarui Wang, Dekui Zhang, Shuyan Li   +9 more
wiley   +1 more source

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ROC SURFACE: A GENERALIZATION OF ROC CURVE ANALYSIS

Journal of Biopharmaceutical Statistics, 2000
Receiver operating characteristic (ROC) curve analysis is widely used in biomedical research to assess the performance of diagnostic tests. Much of the work has been directed at developing accurate indices to describe ROC curves and appropriate statistics to test differences between them.
Harry Yang, David Carlin
openaire   +3 more sources

ROC curves and the binormal assumption

The Journal of Neuropsychiatry and Clinical Neurosciences, 1991
Previous articles in this series have described how receiver operating characteristic (ROC) graphs provide comprehensive graphic representations of the diagnostic performance of non-binary tests and have explained how one constructs "trapezoidal" ROC graphs in which discrete cutoff points are plotted and connected with line segments.
Eugene Somoza, Douglas Mossman
openaire   +3 more sources

Managing bias in ROC curves

Journal of Computer-Aided Molecular Design, 2008
Two modifications to the standard use of receiver operating characteristic (ROC) curves for evaluating virtual screening methods are proposed. The first is to replace the linear plots usually used with semi-logarithmic ones (pROC plots), including when doing "area under the curve" (AUC) calculations.
Robert D. Clark, Daniel J. Webster-Clark
openaire   +2 more sources

On the statistical analysis of ROC curves

Statistics in Medicine, 1989
AbstractWe introduce a new accuracy index for receiver operating characteristic (ROC) curves, namely the partial area under the binormal ROC graph over any specified region of interest. We propose a simple but general procedure, based on a conventional analysis of variance, for comparing accuracy indices derived from two or more different modalities ...
Walter Zucchini, Mary Lou Thompson
openaire   +2 more sources