Search results for "decision tree"

A Machine Learning Approach for Fall Detection Based on the Instantaneous Doppler Frequency

2019

Modern societies are facing an ageing problem that is accompanied by increasing healthcare costs. A major share of this ever-increasing cost is due to fall-related injuries, which urges the development of fall detection systems. In this context, this paper paves the way for the development of radio-frequency-based fall detection systems, which do not require the user to wear any device and can detect falls without compromising the user's privacy. For the design of such systems, we present an activity simulator that generates the complex path gain of indoor channels in the presence of one person performing three different activities: slow fall, fast fall, and walking. We have developed a mac…

2020

Piping erosion is one form of water erosion that leads to significant changes in the landscape and environmental degradation. In the present study, we evaluated piping erosion modeling in the Zarandieh watershed of Markazi province in Iran based on random forest (RF), support vector machine (SVM), and Bayesian generalized linear models (Bayesian GLM) machine learning algorithms. For this goal, due to the importance of various geo-environmental and soil properties in the evolution and creation of piping erosion, 18 variables were considered for modeling the piping erosion susceptibility in the Zarandieh watershed. A total of 152 points of piping erosion were recognized in the study area that…

A methodological comparison of head-cut based gully erosion susceptibility models

2020

Abstract A GIS-based hybrid approach for gully erosion susceptibility mapping (GESM) in the Biarjamand watershed in Iran is presented. A database comprised of 15 geo-environmental factors (GEFs) was compiled and used to predict the spatial distribution of 358 gully locations; 70% (251) of which were extracted for training and 30% (107) for validation. A Dempster-Shafer (DS) statistical model was employed to map susceptibility. Next, the results of four kernels (binary logistic, reg logistic, binary logitraw, and reg linear) of a boosted regression tree (BRT) model were combined to increase the efficiency and accuracy of the mapping. Area under receiver operating characteristics (AUROC), tru…

Multifactorial combinations predicting active vs inactive stages of change for physical activity in adolescents considering built environment and psy…

2018

What grafting materials produce greater alveolar ridge preservation after tooth extraction? A systematic review and network meta-analysis

2021

Abstract A systematic review and network meta-analysis was conducted to compare different bone-substitute materials used for alveolar ridge preservation after tooth extraction. The electronic search was carried out on Embase, PubMed, Cochrane Library, Web of Science, Scopus, LILACS, and grey literature up to March 22, 2020 (registration number INPLASY202030005). Only randomized controlled trials were included to answer the following PICOS question: ‘What grafting materials produce greater alveolar ridge preservation after tooth extraction?’ The primary outcomes were the alveolar width resorption 1 mm below the alveolar crest and buccal height resorption in millimeters. Of the 4379 studies i…

Europäische Leitlinien (S1) für die Anwendung von hochdosierten intravenösen Immunglobulinen in der Dermatologie.

2017

Hintergrund und Ziele Die Behandlung schwerer dermatologischer Autoimmunerkrankungen und der toxischen epidermalen Nekrolyse (TEN) mit hochdosierten intravenosen Immunglobulinen (IVIg) ist ein bewahrtes therapeutisches Verfahren in der Dermatologie. Da eine IVIg‐Therapie in der Regel nur bei seltenen Erkrankungen oder bei schweren Fallen in Betracht gezogen wird, stutzt sich die Anwendung von Immunglobulinen zumeist nicht auf Daten aus randomisierten kontrollierten Studien, wie sie in der evidenzbasierten Medizin erforderlich sind. Da Indikationen fur die Anwendung von IVIg selten sind, ist es unwahrscheinlich, dass solche Studien in absehbarer Zeit durchgefuhrt werden. Wegen der hohen Kost…

Doctoral: A smartphone-based decision support tool for the early detection of oral potentially malignant disorders

2023

Oral potentially malignant disorders can be defined as mucosal lesions and conditions with an increased risk of malignant transformation. Oral potentially malignant disorders are a significant health burden, and they are often diagnosed late due to scant attention to routine dental practice and the low number of specialized oral medicine centres. This report summarizes the DoctOral experience, a research initiative, providing a free smartphone-based decision support tool for the general medical/dental practitioner; the tool is based on the clinical appearance of oral lesions. Captured, oral pictures can be immediately examined via interactive decision trees and constructed on the smartphon…

Evolving Tree Algorithm Modifications

2007

There are many variants of the original self-organizing neural map algorithm proposed by Kohonen. One of the most recent is the Evolving Tree, a tree-shaped self-organizing network which has many interesting characteristics. This network builds a tree structure splitting the input dataset during learning. This paper presents a speed-up modification of the original training algorithm useful when the Evolving Tree network is used with complex data as images or video. After a measurement of the effectiveness an application of the modified algorithm in image segmentation is presented.

Estimating feature discriminant power in decision tree classifiers

1995

Feature Selection is an important phase in pattern recognition system design. Even though there are well established algorithms that are generally applicable, the requirement of using certain type of criteria for some practical problems makes most of the resulting methods highly inefficient. In this work, a method is proposed to rank a given set of features in the particular case of Decision Tree classifiers, using the same information generated while constructing the tree. The preliminary results obtained with both synthetic and real data confirm that the performance is comparable to that of sequential methods with much less computation.

Predicting lorawan behavior. How machine learning can help

2020

Large scale deployments of Internet of Things (IoT) networks are becoming reality. From a technology perspective, a lot of information related to device parameters, channel states, network and application data are stored in databases and can be used for an extensive analysis to improve the functionality of IoT systems in terms of network performance and user services. LoRaWAN (Long Range Wide Area Network) is one of the emerging IoT technologies, with a simple protocol based on LoRa modulation. In this work, we discuss how machine learning approaches can be used to improve network performance (and if and how they can help). To this aim, we describe a methodology to process LoRaWAN packets a…