Search results for "False Positive"
showing 10 items of 64 documents
Automatische Berechnung des Milzvolumens aus Spiral-CT-Daten mit Hilfe neuronaler Netze und „Fuzzy Logik”∗
2000
PURPOSE To assess spleen segmentation and volumentry in spiral CT scans with and without pathological changes of splenic tissue. METHODS The image analysis software HYBRIKON is based on region growing, self-organized neural nets, and fuzzy-anatomic rules. The neural nets were trained with spiral CT data from 10 patients, not used in the following evaluation on spiral CT scans from 19 patients. An experienced radiologist verified the results. The true positive and false positive areas were compared in terms to the areas marked by the radiologist. The results were compared with a standard thresholding method. RESULTS The neural nets achieved a higher accuracy than the thresholding method. Cor…
Lead-time and overdiagnosis estimation in neuroblastoma screening.
2003
In Germany, neuroblastoma is the most frequent extracranial solid childhood tumour. Its properties made it seem an ideal candidate for screening. A German trial assessed the effect of screening at one year of age from 1995-2001 in a nationwide project. We present here the methods developed for the estimation of lead-time and overdiagnosis in this project. Follow up on 1.5 million screened children and 2.1 million control children is currently available until June 2002. Ascertainment of control cohort cases and false negative cases is complete up to this date. A method for determining an empirical lead-time distribution and overdiagnosis estimate from comparing the age specific incidences in…
Evaluation of an Algorithm for Retrospective Hypoglycemia Detection Using Professional Continuous Glucose Monitoring Data.
2014
Background: People with type 1 diabetes (T1D) are unable to produce insulin and thus rely on exogenous supply to lower their blood glucose. Studies have shown that intensive insulin therapy reduces the risk of late-diabetic complications by lowering average blood glucose. However, the therapy leads to increased incidence of hypoglycemia. Although inaccurate, professional continuous glucose monitoring (PCGM) can be used to identify hypoglycemic events, which can be useful for adjusting glucose-regulating factors. New pattern classification approaches based on identifying hypoglycemic events through retrospective analysis of PCGM data have shown promising results. The aim of this study was to…
How to prevent cyber-attacks in inter-vehicle communication network?
2015
In this work, we aim to secure communication in a vehicular network by providing a proactive mechanism that can detect and predict with a high accuracy the future behavior of malicious attacker. In fact, the mechanisms proposed in the literature consider only detection mechanisms and do not prevent attacks that may arise in the network. Simulation results show that our mechanism has a high detection rate, low false positive rate while generating a low communication overhead.
An accurate and efficient collaborative intrusion detection framework to secure vehicular networks
2015
Display Omitted We design and implement an accurate and lightweight intrusion detection framework, called AECFV.AECFV aims to protect the vehicular ad hoc networks (VANETs) against the most dangerous attacks that could occurred on this network.AECFV take into account the VANET's characteristics such as high node's mobility and rapid topology change.AECFV exhibits a high detection rate, low false positive rate, faster attack detection, and lower communication overhead. The advancement of wireless communication leads researchers to develop and conceive the idea of vehicular networks, also known as vehicular ad hoc networks (VANETs). Security in such network is mandatory due to a vital informa…
Efficient on-the-fly Web bot detection
2021
Abstract A large fraction of traffic on present-day Web servers is generated by bots — intelligent agents able to traverse the Web and execute various advanced tasks. Since bots’ activity may raise concerns about server security and performance, many studies have investigated traffic features discriminating bots from human visitors and developed methods for automated traffic classification. Very few previous works, however, aim at identifying bots on-the-fly, trying to classify active sessions as early as possible. This paper proposes a novel method for binary classification of streams of Web server requests in order to label each active session as “bot” or “human”. A machine learning appro…
Prenatal Risk Calculation (PRC) 3.0: An Extended DoE-Based First-Trimester Screening Algorithm Allowing For Early Blood Sampling
2015
Aim: Both previous versions of the German PRC algorithm developed by our group for routine first-trimester screening relied on the assumption that maternal blood sampling and fetal ultrasonography are performed at the same visit of a pregnant women. In this paper we present an extension of our method allowing also for constellations where this synchronization is abandoned through preponing blood sampling to dates before 11 weeks of gestation. Methods: In contrast to the directly measured concentrations of the serum parameters PAPP-A and free ß-hCG, the logarithmically transformed values could be shown to admit the construction of reference bands covering the whole range from 16 to 84 mm CRL…
Compensated transfer entropy as a tool for reliably estimating information transfer in physiological time series
2013
We present a framework for the estimation of transfer entropy (TE) under the conditions typical of physiological system analysis, featuring short multivariate time series and the presence of instantaneous causality (IC). The framework is based on recognizing that TE can be interpreted as the difference between two conditional entropy (CE) terms, and builds on an efficient CE estimator that compensates for the bias occurring for high dimensional conditioning vectors and follows a sequential embedding procedure whereby the conditioning vectors are formed progressively according to a criterion for CE minimization. The issue of IC is faced accounting for zero-lag interactions according to two a…
Automatic detection of lung nodules in CT datasets based on stable 3D mass–spring models
2012
We propose a computer-aided detection (CAD) system which can detect small-sized (from 3 mm) pulmonary nodules in spiral CT scans. A pulmonary nodule is a small lesion in the lungs, round-shaped (parenchymal nodule) or worm-shaped (juxtapleural nodule). Both kinds of lesions have a radio-density greater than lung parenchyma, thus appearing white on the images. Lung nodules might indicate a lung cancer and their early stage detection arguably improves the patient survival rate. CT is considered to be the most accurate imaging modality for nodule detection. However, the large amount of data per examination makes the full analysis difficult, leading to omission of nodules by the radiologist. We…
Value of Neurostimulation Plus Laryngeal Palpation to Predict Postoperative Vocal Fold Motility.
2021
ABSTRACT Background The aim of this study was to evaluate the reliability of intraoperative neuromonitoring through recurrent laryngeal nerve stimulation and simultaneous laryngeal palpation (NSLP) in predicting postoperative vocal cord palsy and in providing useful information in the decision to perform a staged surgery in initially planned total thyroidectomy. Materials and Methods A retrospective review was performed involving 552 patients for whom a total thyroidectomy was planned. In all patients, preoperative and postoperative laryngoscopy was performed. The incidence of vocal cord palsy was calculated on 1104 nerves at risk. Results Sensitivity and specificity of NSLP were 0.9411 and…