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Artificial Intelligence in Medical Applications
2018
Journal of Healthcare Engineering
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Medical artificial intelligence (medical AI) mainly uses computer techniques to perform clinical diagnoses and suggest treatments. ...
results of image classification. ...
Medical artificial intelligence (medical AI) mainly uses computer techniques to perform clinical diagnoses and suggest treatments. ...
doi:10.1155/2018/4827875
pmid:30123442
pmcid:PMC6079562
fatcat:ditffnlgz5fcnoen6ukgfjvhta
Introduction to the Special Issue on Computational Intelligence for Biomedical Data and Imaging
2020
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
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Biologically inspired evolutionary computing algorithms have shown potential for better-performing systems in biomedical and bioinformatics applications. ...
Multi-modal analysis is currently being used for biomedical data for better-performing models. ...
of decision support systems for multi-disciplinary medical treatment. ...
doi:10.1145/3381919
fatcat:taaidy72hzaxjcmrozp6qmmbt4
Hybrid Ensemble Framework for Heart Disease Detection and Prediction
2018
International Journal of Advanced Computer Science and Applications
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intelligent medical decision support systems to improve the ability of the CAD systems in diagnosing heart disease. ...
Data mining techniques have been widely used in clinical decision support systems for detection and prediction of various diseases. ...
The primary concern of artificial intelligence in medicine is construction of an intelligent system that can assist a medical doctor in performing expert diagnosis as well as predicting probability of ...
doi:10.14569/ijacsa.2018.090533
fatcat:bqxkvdmabneelmjs7ydjnmaq3q
Transfer Learning Based Model for Pneumonia Detection in Chest X-ray Images
2021
International Journal of Intelligent Engineering and Systems
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As a result, designing an automated system for detecting pneumonia would be valuable for quickly treating the disease, especially in remote areas. ...
The functionality of the pre-trained EfficientNetB0 model is used as feature-extractors followed by SVM classifier for the classification of abnormal and normal chest X-Rays. ...
International Journal of Intelligent Engineering and Systems, Vol.14, No.5, 2021
DOI: 10.22266/ijies2021.1031.06
Table 4 . 4 Performance matrices for the proposed models Figure. 9 Comparison of Precision ...
doi:10.22266/ijies2021.1031.06
fatcat:56dxthr5i5a4nn5es7dz6hshau
Image Analysis for MRI Based Brain Tumour Detection Using Hybrid Segmentation and Deep Learning Classification Technique
2019
International Journal of Intelligent Engineering and Systems
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In medical image diagnosis, the tumour segmentation and classification schemes are used for identifying the tumour and non-tumour cells in the brain. ...
The performance of Hybrid KFCM-CNN method is validated using T1-Weighted Contrast Enhanced Magnitude Resonance Imaging (T1 -W CEMRI) database. ...
Therefore this research proposes the automatic classification method for classify the brain tumour based on MRI medical image. ...
doi:10.22266/ijies2019.1031.06
fatcat:64qj7jnju5ayrdhxntawpvofmm
Research on Key Algorithms of the Lung CAD System Based on Cascade Feature and Hybrid Swarm Intelligence Optimization for MKL-SVM
2021
Computational Intelligence and Neuroscience
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To improve the performance of the Lung CAD system, algorithmic research is carried out for the above two parts, respectively. ...
Therefore, the MKL-SVM algorithm is presented in this paper, which is based on swarm intelligence optimization is proposed for lung nodule recognition. ...
Improved MKL-SVM Algorithm for Hybrid Swarm Intelligent Optimization Strategy. ...
doi:10.1155/2021/5491017
pmid:34527040
pmcid:PMC8437608
fatcat:uivvlg2wc5a4xgks7zfgvjwfee
An automatic microcalcification detection system based on a hybrid neural network classifier
2002
Artificial Intelligence in Medicine
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A hybrid intelligent system is presented for the identification of microcalcification clusters in digital mammograms. ...
The reduction of false positive cases is performed using an intelligent system containing two subsystems: a rule-based and a neural network sub-system. ...
for Computerized-Aided Detection of Breast Cancer from Radiological Data. ...
doi:10.1016/s0933-3657(02)00013-1
pmid:12031604
fatcat:wg2jzbkw35a2zi56pfjzmqkp44
A SURVEY ON CLASSIFICATION OF LIVER TUMOUR FROM ABDOMINAL COMPUTED TOMOGRAPHY USING MACHINE LEARNING TECHNIQUES
2021
EPRA international journal of research & development
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Several state of art techniques are compared based on performance measures such as accuracy, sensitivity, specificity. Finally, challenges are also highlighted for possible future work. ...
KEYWORDS: Machine Learning, Liver, Liver disease, Computer Aided Diagnosis system, Liver Cancer, Computed Tomography ...
Kondo et al (2011) proposed the hybrid Group Method of Data Handling type neural network algorithm using the artificial intelligence for the medical image diagnosis of liver cancer. ...
doi:10.36713/epra6570
fatcat:g3ln7us6knds3ey3ofeo4kdlra
Table of Contents
2018
2018 Fourth International Conference on Computing Communication Control and Automation (ICCUBEA)
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System For Student Performance Using Data Mining Classification
255
Mathematically Modeled Algorithm For Intelligently Customized Optimization Of An Erp
Track 6: Computer and Communication Security ...
for Improved Content Based Image Classification
189
Heart Rate Measurement From Face And Wrist Video
190
Brain Tumor Extraction from MRI using Clustering Methods and Evaluation of their Performance ...
doi:10.1109/iccubea.2018.8697655
fatcat:jvjgmcrh3fhxtkf4kyydawnkiq
A hybrid deep learning approach towards building an intelligent system for pneumonia detection in chest X-ray images
2021
International Journal of Power Electronics and Drive Systems (IJPEDS)
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A new hybrid artificial intelligence methodology for pneumonia detection has been implemented using small-sized chest X-ray images. ...
The performance of the hybrid systems was comparable to that of the traditional CNN model with Softmax in terms of accuracy, precision, and specificity; except for the RF hybrid system which had less performance ...
The hybrid artificial intelligence system was built using a CNN model that was pretrained on OCT images. ...
doi:10.11591/ijece.v11i6.pp5530-5540
fatcat:hrwfjvm7pzflhe364vb37uquby
BFO – AIS: A Framework for Medical Image Classification Using Soft Computing Techniques
2017
International Journal of Soft Computing
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This paper proposes an Artificial Immune System (AIS) classifier and proposed feature selection based on hybrid Bacterial Foraging Optimization (BFO) with Local Search (LS) for medical image classification ...
Medical information systems goals are to deliver information to right persons at the right time and place to improve care process quality and efficiency. ...
This paper used an AIS classifier with hybrid BFO for medical images classification. Results proved that the new method improved performance over other classifiers and feature selection methods. ...
doi:10.5121/ijsc.2017.8102
fatcat:zqlxihtwl5h6pjwmuahtbejhsa
Improved Segmentation algorithm using PSO and K-means for Basal Cell Carcinoma Classification from Skin Lesions
2019
VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE
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for BCC. ...
The proposed system is evaluated using the largest publicly accessible standard skin lesions dataset of dermoscopic images, containing BCC and Non-BCC images. ...
For the detection and classification of skin diseases, segmentation of skin lesions is major task and it is performed by hybridization of K-means with PSO. ...
doi:10.35940/ijitee.i1113.0789s419
fatcat:lql45yxd4bbvjn2g6facrlqh2e
Detection of Breast Cancer on Magnetic Resonance Imaging Using Hybrid Feature Extraction and Deep Neural Network Techniques
2020
International Journal of Intelligent Engineering and Systems
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The performance of the proposed hybrid LOOP Haralick feature extraction shows significant accuracy improvement of 3.83% when compared to the Haralick feature extraction technique. ...
The treatment for the breast cancer at an early stage is important using Magnetic Resonance Imaging (MRI) which effectively measures the size of the cancer and also checks tumors in the opposite breast ...
The classification is performed based on the hybrid parameters using SAE to classify the breast MRI image as a Malignant or Benign. ...
doi:10.22266/ijies2020.1231.21
fatcat:7qmollp2anh33pqgly6s6jda64
An efficient of estimation stages for segmentation skin lesions based optimization algorithm
2021
International Journal of Power Electronics and Drive Systems (IJPEDS)
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It is calculated to survey a different metaheuristic and evolutionary computing working for filter design systems. ...
The design of MF depends on modern artificial swarm intelligence technique (MASIT) optimization algorithm which has proven to be more effective than other population-based algorithms to improve of estimation ...
There are many steps for improving the hybrid feature classification using segmentation of digital filter with ABC approach to make early decision of dermatology as shown in Figure 4 have been discussed ...
doi:10.11591/ijece.v11i1.pp402-408
fatcat:ckzgsddnznbetm4rd57veukkta
Two-Stage Classification Model for the Prediction of Heart Disease Using IoMT and Artificial Intelligence
2022
Sensors
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for echocardiogram image classification. ...
In the first stage, data gathered from medical sensors affixed to the patient's body were classified; then, in stage two, echocardiogram image classification was performed for heart disease prediction. ...
Informed Consent Statement: No animals/humans were used for studies that are the basis of this research. ...
doi:10.3390/s22020476
pmid:35062437
pmcid:PMC8778567
fatcat:egcollxztbdc5n7qxihsif6kl4
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