• Publications
  • Influence
Multiperiod Corporate Default Prediction - A Forward Intensity Approach
A forward intensity model for the prediction of corporate defaults over different future periods is proposed. Maximum pseudo-likelihood analysis is then conducted on a large sample of the USExpand
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  • 22
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Predicting financial distress and corporate failure: A review from the state-of-the-art definitions, modeling, sampling, and featuring approaches
TLDR
The current literatures of FDP are reviewed from the following four unique aspects: definition of financial distress in the new century, FDP modeling, sampling approaches, and featuring approaches for FDP. Expand
  • 179
  • 6
Financial distress prediction based on OR-CBR in the principle of k-nearest neighbors
TLDR
In this study, outranking relations (OR), including strict difference, weak difference, and indifference, between cases on each feature are introduced to build up a new feature-based similarity measure mechanism in the principle of k-nearest neighbors. Expand
  • 74
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Financial distress prediction using support vector machines: Ensemble vs. individual
  • J. Sun, H. Li
  • Computer Science
  • Appl. Soft Comput.
  • 1 August 2012
TLDR
We propose a new FDP method based on SVM ensemble, whose candidate single classifiers are trained by SVM algorithms with different kernel functions on different feature subsets of one initial dataset. Expand
  • 86
  • 5
Predicting business failure using multiple case-based reasoning combined with support vector machine
  • H. Li, J. Sun
  • Mathematics, Computer Science
  • Expert Syst. Appl.
  • 1 August 2009
TLDR
We develop a new combining-classifiers system for financial distress prediction, where four independent CBR systems with k-nearest neighbor (KNN) algorithms are employed as classifiers to be combined, and SVM is utilized as the algorithm fulfilling combining- classifiers. Expand
  • 83
  • 5
Listed companies' financial distress prediction based on weighted majority voting combination of multiple classifiers
  • J. Sun, H. Li
  • Computer Science
  • Expert Syst. Appl.
  • 1 October 2008
TLDR
This paper puts forward a financial distress prediction method based on weighted majority voting combination of multiple classifiers that can greatly improve the average prediction accuracy and stability. Expand
  • 97
  • 4
Ranking-order case-based reasoning for financial distress prediction
  • H. Li, J. Sun
  • Computer Science
  • Knowl. Based Syst.
  • 1 December 2008
TLDR
ROCBR outperforms ECBR, MCBR, ICBR, MDA, and Logit significantly in financial distress prediction of Chinese listed companies 1 year prior to distress, if irrelevant information has been handled effectively. Expand
  • 123
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Germline Mutations in Cancer Susceptibility Genes in a Large Series of Unselected Breast Cancer Patients
Purpose: The prevalence of mutations in cancer susceptibility genes such as BRCA1 and BRCA2 and other cancer susceptibility genes and their clinical relevance are largely unknown among a large seriesExpand
  • 70
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Business failure prediction using hybrid2 case-based reasoning (H2CBR)
  • H. Li, J. Sun
  • Mathematics, Computer Science
  • Comput. Oper. Res.
  • 2010
TLDR
We have investigated business failure prediction (BFP) by combining various outranking preference functions with case-based reasoning (CBR), whose heart is the k-nearest neighbor (k-NN) algorithm, and empirically test the predictive performance of its modules. Expand
  • 48
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Cost-effectiveness of nivolumab plus ipilimumab as first-line therapy in advanced renal-cell carcinoma
BackgroundNivolumab plus ipilimumab improves overall survival and is associated with less toxicity compared with sunitinib in the first-line setting of advanced renal-cell carcinoma (RCC). TheExpand
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