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Artificial Intelligence in Medical Applications

Yung-Kuan Chan, Yung-Fu Chen, Tuan Pham, Weide Chang, Ming-Yuan Hsieh
2018 Journal of Healthcare Engineering  
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

M. Tanveer, P. Khanna, M. Prasad, C. T. Lin
2020 ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)  
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

Elham Nikookar, Ebrahim Naderi
2018 International Journal of Advanced Computer Science and Applications  
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

Ola Zein, Al-Azhar University (Girls branch), Mona Soliman, A Elkholy, Neveen Ghali, Cairo University, Al-Azhar University (Girls branch), Future University in Egypt
2021 International Journal of Intelligent Engineering and Systems  
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

Sudheesh Rao, Academy for Technical and Management Excellence College of Engineering, Basavaraj Lingappa, Academy for Technical and Management Excellence College of Engineering
2019 International Journal of Intelligent Engineering and Systems  
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

Jiayue Chang, Yang Li, Hewei Zheng, Rodolfo E. Haber
2021 Computational Intelligence and Neuroscience  
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

A. Papadopoulos, D.I. Fotiadis, A. Likas
2002 Artificial Intelligence in Medicine  
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


Gunasundari S, Swetha R
2021 EPRA international journal of research & development  
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)  
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

Ihssan S. Masad, Amin Alqudah, Ali Mohammad Alqudah, Sami Almashaqbeh
2021 International Journal of Power Electronics and Drive Systems (IJPEDS)  
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

Chitra D, Karthikeyan M
2017 International Journal of Soft Computing  
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

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

Nagaraja Pullaiah, Annamalai University, Dorai Venkatasekhar, Padarthi Venkatramana, Balaraj Sudhakar, Annamalai University, Sree Vidyanikethan Engineering College, Annamalai University
2020 International Journal of Intelligent Engineering and Systems  
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

Nooraldeen Raaoof Hadi, H. K. Latif, Mohanad Aljanabi
2021 International Journal of Power Electronics and Drive Systems (IJPEDS)  
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

S. Manimurugan, Saad Almutairi, Majed Mohammed Aborokbah, C. Narmatha, Subramaniam Ganesan, Naveen Chilamkurti, Riyadh A. Alzaheb, Hani Almoamari
2022 Sensors  
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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