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Computer-aided diagnosis of lumbar stenosis conditions

Soontharee Koompairojn, Kathleen Hua, Kien A. Hua, Jintavaree Srisomboon, Nico Karssemeijer, Ronald M. Summers
2010 Medical Imaging 2010: Computer-Aided Diagnosis  
Features can then be extracted from these spinal components. Finally, diagnosis is done by applying a Multilayer Perceptron.  ...  The trained Perceptron can then be applied to diagnose new cases for various spinal conditions.  ...  Spinal component segmentation using multilayer perceptron The output of the MLP indicates the type of the pixel.  ... 
doi:10.1117/12.844545 dblp:conf/micad/KoompairojnHHS10 fatcat:acpjryyfxfaqhlfhobhlmvfemm

Review on Brain Tumor Detection and Segmentation Techniques

Mansa SMane, Nikita J Kulkarni, Santosh N Randive
2014 International Journal of Computer Applications  
Detection of brain tumor area is crucial for irregular shapes and their diverse volumes. This paper discusses on study of various brain tumor detection and segmentation techniques.  ...  Kavitha et al [5] used a combination of watershed and thresholding algorithm on multilayer perceptron for segmentation of brain tumor in MRI.  ...  Technique 4: Watershed, Thresholding, Multilayer Perceptron (MLP), Peak signal to noise ratio (PSNR).  ... 
doi:10.5120/16593-6307 fatcat:w3ulhq7j55dehcqyrwum6lqtye

A Supervised Machine Learning Approach to Characterize Spinal Network Function

Ashley N Dalrymple, Simon A Sharples, Nathan Osachoff, Adam Parker Lognon, Patrick J. Whelan
2019 Journal of Neurophysiology  
Paired classes and features were used to train and test supervised machine learning algorithms. Multilayer perceptrons were used to classify episodes as rhythmic or multi-burst.  ...  Supervised machine learning-based classification of episodes accounted for changes that traditional approaches cannot detect.  ...  MULTILAYER PERCEPTRONS.  ... 
doi:10.1152/jn.00763.2018 pmid:30943091 pmcid:PMC6620704 fatcat:fuczkx7sxbchndzzk3y3cb47ye

Neural network model for transient ischemic attacks diagnostics

V. Golovko, Henadzi Vaitsekhovich, E. Apanel, A. Mastykin
2012 Optical Memory and Neural Networks  
The proposed approach is based on integration of the NPCA neural network and multilayer perceptron. The dataset from clinic have been used for experiments performing.  ...  Combining two different neural networks (NPCA and MLP) it is possible to produce efficient performance in terms of detection and recognition transient ischemic attacks.  ...  The backpropagation algorithm is used for training multilayer perceptron.  ... 
doi:10.3103/s1060992x12030095 fatcat:srxu4tok3vbuhdhsfrkm323fay

Data-driven diagnosis of spinal abnormalities using feature selection and machine learning algorithms

Md. Raihan-Al-Masud, M. Rubaiyat Hossain Mondal, María Angeles Pérez
2020 PLoS ONE  
This paper focuses on the application of machine learning algorithms for predicting spinal abnormalities.  ...  A number of machine learning approaches namely support vector machine (SVM), logistic regression (LR), bagging ensemble methods are considered for the diagnosis of spinal abnormality.  ...  In the work [17] , both base and meta-level classification algorithms such as naïve Bayes, Bayes net, multilayer perceptron (MLP), random forest, decision table are applied.  ... 
doi:10.1371/journal.pone.0228422 pmid:32027680 fatcat:mk5dsu2w6vcblatw4vhnfat6ka

A Machine Learning Approach on Classifying Orthopedic Patients Based on Their Biomechanical Features

Kamrul Hasan, Safkat Islam, Md. Mehfil Rashid Khan Samio, Amitabha Chakrabarty
2018 2018 Joint 7th International Conference on Informatics, Electronics & Vision (ICIEV) and 2018 2nd International Conference on Imaging, Vision & Pattern Recognition (icIVPR)  
Application of machine learning algorithms in medical science is not new. Different algorithms are applied to detect diseases and classify patients accordingly.  ...  In this paper we have applied various machine learning algorithms to find out which one works most accurately to detect and classify orthopedic patients.  ...  Multi-Layer Perceptron Multilayer perception is a supervised learning algorithm. MLP has multiple nodes arranged in interconnected layers named input, hidden and output layers.  ... 
doi:10.1109/iciev.2018.8641042 fatcat:usqbx4wq3fdq7mbd5x7mt5elh4

Review on different Brain Tumor Analysis Techniques

Amit D. Mudukshiwale
2019 International Journal for Research in Applied Science and Engineering Technology  
Sobel edge detection based improved edge detection algorithm provide superior performance over conventional segmentation algorithm K-Mean algorithm used  ...  Magnetic Resonance Imaging (MRI), Computer Tomography (CT) imaging techniques are used for early detection of abnormal changes in tumor tissues or cells.  ...  detailed information is extracted 7 P.Sangeetha et al. 2014 PNN Gives the maximum tumor recognition rate PNN are slower than multilayer perceptron networks at classifying new cases. 8  ... 
doi:10.22214/ijraset.2019.5289 fatcat:pjswccic7jedndnpy6u7el5wai

Tracking Foot Drop Recovery Following Lumbar-Spine Surgery, Applying Multiclass Gait Classification Using Machine Learning Techniques

Shiva Sharif Bidabadi, Tele Tan, Iain Murray, Gabriel Lee
2019 Sensors  
The results revealed that the random forest algorithm performed best out of the selected ML algorithms, with an overall 84.89% classification accuracy and 0.3785 mean absolute error for regression.  ...  Various machine learning (ML) algorithms were applied to categorize the data into specific groups associated with the recovery stages.  ...  of gait patterns at different stages of spinal surgery treatment.  ... 
doi:10.3390/s19112542 fatcat:ipxzwaqdwfgvbo2snuwcxkerla

A Review on the Use of Artificial Intelligence in Spinal Diseases

Parisa Azimi, Taravat Yazdanian, Edward C. Benzel, Hossein Nayeb Aghaei, Shirzad Azhari, Sohrab Sadeghi, Ali Montazeri
2020 Asian Spine Journal  
The evidence suggests that ANNs can be successfully used for optimizing the diagnosis, prognosis and outcome prediction in spinal diseases.  ...  Artificial neural networks (ANNs) have been used in a wide variety of real-world applications and it emerges as a promising field across various branches of medicine.  ...  ANN, artificial neural network; MLP, multilayer perceptron neural networks; LBP, low back pain; LR, logistic regression; ROC, receiver operating characteristic; SE, standard error; SVM, support vector  ... 
doi:10.31616/asj.2020.0147 pmid:32326672 pmcid:PMC7435304 fatcat:cxdxp3jpurcgzp2hjne5mrj5qu


Nur Farahana Zainudin, Norizan Mohamed, Nor Azlida Aleng, Siti Hasliza Ahmad Rusmili
2015 Jurnal Teknologi  
Next, the result of SPSS software will be used and run by MATLAB software.  ...  The real data from UCI Machine Learning websites that used 500 Parkinson's patients and 7 different attributes as the subject were analyzed by using Statistical Package for Social Sciences (SPSS) 21.0.  ...  They are a 4 possible diagnosis result, such as simple lower back pain (SLBP), root pain (RP), spinal pain (SP) and abnormal illness behavior (AIB).  ... 
doi:10.11113/jt.v77.7014 fatcat:kv3jctodbjh4rda6yloxboglyi

Medical Big Data: Neurological Diseases Diagnosis Through Medical Data Analysis

Siuly Siuly, Yanchun Zhang
2016 Data Science and Engineering  
Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecomm, which permits unrestricted use, distribution  ...  The classification process was performed into partial and primary generalised epilepsy by employing RBFNN and multilayer perceptron neural network (MLPNNs).  ...  To investigate spinal nerve injury, herniated discs, fractures, back or leg pain and spinal tumours, myelograms are used.  ... 
doi:10.1007/s41019-016-0011-3 fatcat:gdebiikzjvghjaegsggrpmz24q

A narrative review of machine learning as promising revolution in clinical practice of scoliosis

Kai Chen, Xiao Zhai, Kaiqiang Sun, Haojue Wang, Changwei Yang, Ming Li
2021 Annals of Translational Medicine  
By implementing its algorithms, our ability to detect previously undiscoverable patterns in data has the potential to revolutionize predictive analytics.  ...  Additionally, current limitations and future directions are briefly discussed regarding its use in the field of scoliosis.  ...  Study Year Number of data Algorithms applied Objectives Outcome presentation Zareie (47) 2018 18 3D vertebrae CT images of thoracic and lumbar spine Multilayer perceptron neural network; pulse  ... 
doi:10.21037/atm-20-5495 pmid:33553360 pmcid:PMC7859734 fatcat:ohnalkrwdncvvc4zvdcnhjcyam

Breast Cancer Detection and Classification Using Deep CNN Techniques

R. Rajakumari, L. Kalaivani
2022 Intelligent Automation and Soft Computing  
Early detection, a personalized treatment approach, and better understanding are necessary for cancer patients to survive.  ...  In the latter part of this study, particle swarm optimization-based multi-layer perceptron (PSO-MLP) and ant colony optimization-based multi-layer perceptron (ACO-MLP) were employed for breast cancer recognition  ...  Multilayer Perceptron A multilayer perceptron (MLP) is a feed-forward artificial neural network (ANN).  ... 
doi:10.32604/iasc.2022.020178 fatcat:ybcx6bpzvnf7tnv3t3mmvp226y

Medical Applications of Fuzzy Logic in Pattern Recognition

Metin Akay, Attila Medl, Gregory Ciresi
1997 International journal of biomedical soft computing and human sciences  
in this paper we review the concept ofpattem recognition, clustering algorithms and neural networks forpattem recqgnition, in addition, the imptementations of these algorithms are ddscussed in detail.  ...  Finally, the medicat applications of fuziy logic based pattem recopnition algorithms are presented.  ...  Multilayer perceptrons were fuzzified for speech recognition [301.  ... 
doi:10.24466/ijbschs.3.1_1 fatcat:naamvyyvmzbppcjcffk2mrkqgu

A Survey on Brain Tumor Detection and Classification System based on Artificial Neural Network

Priya Kochar
2014 International Journal of Computer Applications  
Tumour detection is done initially by MRI , BIOPSY , SPINAL TAPE TEST ,ANNINOGARM and by some other similar kind of tests. All these tests are not only painful but are expensive too.  ...  SMO when used with kmeans clustering provides a more accurate system.  ...  RBF networks have the advantage of not being locked into local minima as do the feed-forward networks such as the multilayer perceptron. .  ... 
doi:10.5120/15820-4651 fatcat:7xasiedkabgwlnxewuo4vb6a2y
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