Results 181 to 190 of about 302,402 (283)

Prediction of Lung Cancer Metastasis Risk Based on Single‐Cell Metabolic Profiling of Circulating Tumor Cells

Advanced Science, EarlyView.
A self‐developed CTC sorting and capture platform enabled single‐cell metabolomics of patient/animal CTCs, revealing brain/bone metastasis‐specific metabolic signatures. A classification model developed from these signatures predicted lung cancer metastasis risk, outperforming traditional markers and total CTC counts (AUCs:89 brain = 0.74; bone = 0.92).
Yang Xu, Xuesen Hu, Yuan Yuan, Wenwen Liu, Jian Wang, Chunhui Yang, Xianzhe Shi, Wangshu Qin, Liliang Wen, Manqing Lin, Yinuo Jin, Wei Wang, Chunxiu Hu, Guowang Xu, Qi Wang   +14 more
wiley   +1 more source

Ready to ROC? A tutorial on simulation-based power analyses for null hypothesis significance, minimum-effect, and equivalence testing for ROC curve analyses. [PDF]

Behav Res Methods
Riesthuis P, Otgaar H, Bücken C.
europepmc   +1 more source

Use of likelihood ratios for comparisons of binary diagnostic tests: Underlying ROC curves [PDF]

, 2010
Andriy I. Bandos, Howard E. Rockette, David Gur   +2 more
openalex   +1 more source

Artificial Intelligence‐Assisted Urine Cytology for Noninvasive Detection of Muscle‐Invasive Urothelial Carcinoma: A Multi‐Center Diagnostic Study with Prospective Validation

Advanced Science, EarlyView.
Accurate preoperative detection of muscle‐invasive urothelial carcinoma (MIUC) is crucial for clinical decision‐making. This study developed PUCAS‐M, an artificial intelligence (AI) model that analyzes urine cytology to assist in differentiating MIUC from non‐MIUC.
Runnan Shen, Fan Jiang, Xiaowei Huang, Guibin Hong, Yun Luo, Huan Wan, Ye Xie, Mengyi Zhu, Yun Wang, Bohao Liu, Ping Qin, Yahui Wang, Haoxuan Wang, Hongkun Yang, Zhen Lin, Rui Chen, Nengtai Ouyang, Jian Huang, Tianxin Lin, Shaoxu Wu   +19 more
wiley   +1 more source

Performance of tests based on the area under the ROC curve for multireader diagnostic data. [PDF]

J Appl Stat
Hwang YT, Hsu YR, Su NC.
europepmc   +1 more source

Biomolecular Interaction Prediction: The Era of AI

Advanced Science, EarlyView.
This review offers a thorough examination of recent progress in deep learning for predicting biomolecular interactions, including those involving proteins, nucleic acids, and small molecules. It covers data processing strategies, representative model architectures, and evaluation metrics, while highlighting current methodological limitations.
Haoping Wang, Xiangjie Meng, Yang Zhang
wiley   +1 more source

ROC curve analysis: a useful statistic multi-tool in the research of nephrology. [PDF]

Int Urol Nephrol
Roumeliotis S, Schurgers J, Tsalikakis DG, D'Arrigo G, Gori M, Pitino A, Leonardis D, Tripepi G, Liakopoulos V.   +8 more
europepmc   +1 more source

Artificial Intelligence‐Driven Proteomics Identifies Plasma Protein Signatures for Diagnosis and Stratification of Behçet's Disease

Advanced Science, EarlyView.
Molecular and functional landscape of BD progression and severity based on in‐depth proteomics. Tree boosting machine learning models with favorable performance in BD diagnosis and stratification. Efficient biomarker panels for BD diagnosis and stratification. .
Linlin Cheng, Mansheng Li, Zhou Bai, Xiaobo Yu, Wenjie Zheng, Yongzhe Li, Yudong Liu   +6 more
wiley   +1 more source

An alternative parameterization for the binormal ROC curve, with applications to sizing and simulation studies. [PDF]

Proc SPIE Int Soc Opt Eng
Hillis SL.
europepmc   +1 more source