Interval Coded Scoring: a toolbox for interpretable scoring systems.

Over the last decades, clinical decision support systems have been gaining importance. They help clinicians to make effective use of the overload of available information to obtain correct diagnoses and appropriate treatments. However, their power often comes at the cost of a black box model which cannot be interpreted easily.

Explaining Support Vector Machines: A Color Based Nomogram.

Problem Setting: Support vector machines (SVMs) are very popular tools for classification, regression and other problems. Due to the large choice of kernels they can be applied with, a large variety of data can be analysed using these tools. Machine learning thanks its popularity to the good performance of the resulting models.

Visualizing Risk Prediction Models.

Objective: Risk prediction models can assist clinicians in making decisions. To boost the uptake of these models in clinical practice, it is important that end-users understand how the model works and can efficiently communicate its results. We introduce novel methods for interpretable model visualization.

Evaluating the risk of ovarian cancer before surgery using the ADNEX model to differentiate between benign, borderline, early and advanced stage invasive, and secondary metastatic tumours: prospective multicentre diagnostic study.

Objectives: To develop a risk prediction model to preoperatively discriminate between benign, borderline, stage I invasive, stage II-IV invasive, and secondary metastatic ovarian tumours.

Design: Observational diagnostic study using prospectively collected clinical and ultrasound data.

Setting: 24 ultrasound centres in 10 countries.

Prognostic value of serum HE4 levels and risk of ovarian malignancy algorithm scores at the time of ovarian cancer diagnosis.

Objectives: The aim of this study is to assess whether the pretreatment serum HE4 levels or the Risk of Ovarian Malignancy Algorithm (ROMA) scores at the time of initial diagnosis are associated with progression-free survival (PFS) and disease-specific survival (DSS) in patients with ovarian cancer receiving either primary debulking surgery or neoadjuvant chemotherapy followed by interval debulking surgery.

Methods: A survival analysis of 101 cases of invasive ovarian cancer recruited in a previous diagnostic accuracy study was conducted from 2005 to 2009 at the University Hospital KU Leuven, Belgium. Serum HE4 levels (pM) and ROMA scores (%) were obtained before primary treatment.

White box radial basis function classifiers with component selection for clinical prediction models.

Objective: To propose a new flexible and sparse classifier that results in interpretable decision support systems.

Methods: Support vector machines (SVMs) for classification are very powerful methods to obtain classifiers for complex problems. Although the performance of these methods is consistently high and non-linearities and interactions between variables can be handled efficiently when using non-linear kernels such as the radial basis function (RBF) kernel, their use in domains where interpretability is an issue is hampered by their lack of transparency.

Accurate prediction of pregnancy viability by means of a simple scoring system.

Study Question: What is the performance of a simple scoring system to predict whether women will have an ongoing viable intrauterine pregnancy beyond the first trimester?

Summary Answer: A simple scoring system using demographic and initial ultrasound variables accurately predicts pregnancy viability beyond the first trimester with an area under the curve (AUC) in a receiver operating characteristic curve of 0.924 [95% confidence interval (CI) 0.900-0.

Assessing the discriminative ability of risk models for more than two outcome categories.

The discriminative ability of risk models for dichotomous outcomes is often evaluated with the concordance index (c-index). However, many medical prediction problems are polytomous, meaning that more than two outcome categories need to be predicted. Unfortunately such problems are often dichotomized in prediction research.

Extending the c-statistic to nominal polytomous outcomes: the Polytomous Discrimination Index.

Diagnostic problems in medicine are sometimes polytomous, meaning that the outcome has more than two distinct categories. For example, ovarian tumors can be benign, borderline, primary invasive, or metastatic. Extending the main measure of binary discrimination, the c-statistic or area under the ROC curve, to nominal polytomous settings is not straightforward.

Discrimination ability of prediction models for ordinal outcomes: relationships between existing measures and a new measure.

In this paper, we focus on measures to evaluate discrimination of prediction models for ordinal outcomes. We review existing extensions of the dichotomous c-index-which is equivalent to the area under the receiver operating characteristic (ROC) curve--suggest a new measure, and study their relationships. The volume under the ROC surface (VUS) scores sets of cases including one case from each outcome category.

A mathematical model for interpretable clinical decision support with applications in gynecology.

Background: Over time, methods for the development of clinical decision support (CDS) systems have evolved from interpretable and easy-to-use scoring systems to very complex and non-interpretable mathematical models. In order to accomplish effective decision support, CDS systems should provide information on how the model arrives at a certain decision. To address the issue of incompatibility between performance, interpretability and applicability of CDS systems, this paper proposes an innovative model structure, automatically leading to interpretable and easily applicable models.

Support vector methods for survival analysis: a comparison between ranking and regression approaches.

Objective: To compare and evaluate ranking, regression and combined machine learning approaches for the analysis of survival data.

Methods: The literature describes two approaches based on support vector machines to deal with censored observations. In the first approach the key idea is to rephrase the task as a ranking problem via the concordance index, a problem which can be solved efficiently in a context of structural risk minimization and convex optimization techniques.

Qualitative assessment of the progesterone receptor and HER2 improves the Nottingham Prognostic Index up to 5 years after breast cancer diagnosis.

Purpose: To investigate whether the estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) can improve the Nottingham Prognostic Index (NPI) in the classification of patients with primary operable breast cancer for disease-free survival (DFS).

Patients And Methods: The analysis is based on 1,927 patients with breast cancer treated between 2000 and 2005 at the University Hospitals, Leuven. We compared performances of NPI with and without ER, PR and/or HER2.

Short-term outcome of primary operated early breast cancer by hormone and HER-2 receptors.

Introduction: Prognostic subgroup classification of operable breast cancers using cDNA clustering of breast cancer-related genes resembles the classification based on the combined immunohistochemical (IHC) expression of the hormone and HER-2 receptors. We here report the short-term disease-free interval (DFI) of operable breast cancers by their joint hormone receptor/HER-2 phenotype.

Patients And Methods: Short-term follow-up (FU) of a prospective cohort of 1,958 breast-cancer patients primary operated at our institution between 2000 and 2005.

Plasma MMP1 and MMP8 expression in breast cancer: protective role of MMP8 against lymph node metastasis.

Background: Elevated levels of matrix metalloproteinases have been found to associate with poor prognosis in various carcinomas. This study aimed at evaluating plasma levels of MMP1, MMP8 and MMP13 as diagnostic and prognostic markers of breast cancer.

Methods: A total of 208 breast cancer patients, of which 21 with inflammatory breast cancer, and 42 healthy controls were included.