AIMC Topic: Sensitivity and Specificity

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Outlier detection and removal improves accuracy of machine learning approach to multispectral burn diagnostic imaging.

Journal of biomedical optics
Multispectral imaging (MSI) was implemented to develop a burn tissue classification device to assist burn surgeons in planning and performing debridement surgery. To build a classification model via machine learning, training data accurately represen...

Detection of Hard Exudates in Colour Fundus Images Using Fuzzy Support Vector Machine-Based Expert System.

Journal of digital imaging
Diabetic retinopathy is a major cause of vision loss in diabetic patients. Currently, there is a need for making decisions using intelligent computer algorithms when screening a large volume of data. This paper presents an expert decision-making syst...

[Analysis of risk factors for prognosis of patients with acute paraquat intoxication].

Zhonghua wei zhong bing ji jiu yi xue
OBJECTIVE: To explore the risk factors influencing the prognosis by analyzing clinical data of patients with acute paraquat intoxication, and to assess the prognostic values of acute physiology and chronic health evaluation II (APACHE II) score, sequ...

Protein-protein interaction site prediction in Homo sapiens and E. coli using an interaction-affinity based membership function in fuzzy SVM.

Journal of biosciences
Protein-protein interaction (PPI) site prediction aids to ascertain the interface residues that participate in interaction processes. Fuzzy support vector machine (F-SVM) is proposed as an effective method to solve this problem, and we have shown tha...

SPEQTACLE: An automated generalized fuzzy C-means algorithm for tumor delineation in PET.

Medical physics
PURPOSE: Accurate tumor delineation in positron emission tomography (PET) images is crucial in oncology. Although recent methods achieved good results, there is still room for improvement regarding tumors with complex shapes, low signal-to-noise rati...

An Efficient Approach for Automated Mass Segmentation and Classification in Mammograms.

Journal of digital imaging
Breast cancer is becoming a leading death of women all over the world; clinical experiments demonstrate that early detection and accurate diagnosis can increase the potential of treatment. In order to improve the breast cancer diagnosis precision, th...

An Artificial Immune System-Based Support Vector Machine Approach for Classifying Ultrasound Breast Tumor Images.

Journal of digital imaging
A rapid and highly accurate diagnostic tool for distinguishing benign tumors from malignant ones is required owing to the high incidence of breast cancer. Although various computer-aided diagnosis (CAD) systems have been developed to interpret ultras...

The Role of Thyrotropin-Releasing Hormone Stimulation Test in Management of Hyperthyrotropinemia in Infants.

Journal of clinical research in pediatric endocrinology
OBJECTIVE: Hyperthyrotropinemia, which can be either a permanent or a transient state, is an asymptomatic condition and there is a controversy in management and long-term consequences. The aim of this study was to evaluate the results of thyrotropin-...

Improving medical diagnosis reliability using Boosted C5.0 decision tree empowered by Particle Swarm Optimization.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Improving accuracy of supervised classification algorithms in biomedical applications is one of active area of research. In this study, we improve the performance of Particle Swarm Optimization (PSO) combined with C4.5 decision tree (PSO+C4.5) classi...