AIMC Topic: Algorithms

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Detection of coronavirus disease from X-ray images using deep learning and transfer learning algorithms.

Journal of X-ray science and technology Jan 1, 2020
OBJECTIVE: This study aims to employ the advantages of computer vision and medical image analysis to develop an automated model that has the clinical potential for early detection of novel coronavirus (COVID-19) infected disease.
Pneumonia, Viral Pneumonia Coronavirus Infections COVID-19 SARS-CoV-2 Early Diagnosis Betacoronavirus Algorithms Lung Tomography, X-Ray Computed Deep Learning Humans Reproducibility of Results Neural Networks, Computer Pandemics
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Identification of COVID-19 samples from chest X-Ray images using deep learning: A comparison of transfer learning approaches.

Journal of X-ray science and technology Jan 1, 2020
BACKGROUND: The novel coronavirus disease 2019 (COVID-19) constitutes a public health emergency globally. The number of infected people and deaths are proliferating every day, which is putting tremendous pressure on our social and healthcare system. ...
Betacoronavirus Pneumonia, Viral Pandemics Diagnosis, Differential COVID-19 Tomography, X-Ray Computed Pneumonia Algorithms Reproducibility of Results Coronavirus Infections Databases, Factual Humans SARS-CoV-2 Radiography, Thoracic Neural Networks, Computer Deep Learning
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Electroencephalogram-Based Emotion Recognition Using a Particle Swarm Optimization-Derived Support Vector Machine Classifier.

Critical reviews in biomedical engineering Jan 1, 2020
We sort human emotions using Russell's circumplex model of emotion by classifying electroencephalogram (EEG) signals from 25 subjects into four discrete states, namely, happy, sad, angry, and relaxed. After acquiring signals, we use a standard databa...
Adult Male Deep Learning Adolescent Support Vector Machine Emotions Electroencephalography Algorithms Female Reproducibility of Results Young Adult Humans Wavelet Analysis Recognition, Psychology Signal Processing, Computer-Assisted Electrodes Pattern Recognition, Automated
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Automated Gleason grading of prostate cancer using transfer learning from general-purpose deep-learning networks.

Romanian journal of morphology and embryology = Revue roumaine de morphologie et embryologie Jan 1, 2020
Two deep-learning algorithms designed to classify images according to the Gleason grading system that used transfer learning from two well-known general-purpose image classification networks (AlexNet and GoogleNet) were trained on Hematoxylin-Eosin h...
Male Deep Learning Prostatic Neoplasms Neoplasm Grading Humans Algorithms
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Classification of Benign and Malignant Breast Masses on Mammograms for Large Datasets using Core Vector Machines.

Current medical imaging Jan 1, 2020
BACKGROUND: Breast cancer is one of the most leading causes of cancer deaths among women. Early detection of cancer increases the survival rate of the affected women. Machine learning approaches that are used for classification of breast cancer usual...
Breast Diseases Early Detection of Cancer Mammography Datasets as Topic Radiographic Image Enhancement Sensitivity and Specificity Breast Neoplasms Support Vector Machine Humans Neural Networks, Computer Algorithms Female
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A Survey on Machine Learning Algorithms for the Diagnosis of Breast Masses with Mammograms.

Current medical imaging Jan 1, 2020
Breast cancer is leading cancer among women for the past 60 years. There are no effective mechanisms for completely preventing breast cancer. Rather it can be detected at its earlier stages so that unnecessary biopsy can be reduced. Although there ar...
Radiologists Breast Diagnosis, Computer-Assisted Surveys and Questionnaires Mammography Humans Neural Networks, Computer Machine Learning Algorithms Female Breast Neoplasms
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Deployment of Artificial Intelligence in Real-World Practice: Opportunity and Challenge.

Asia-Pacific journal of ophthalmology (Philadelphia, Pa.) Jan 1, 2020
Artificial intelligence has rapidly evolved from the experimental phase to the implementation phase in many image-driven clinical disciplines, including ophthalmology. A combination of the increasing availability of large datasets and computing power...
Artificial Intelligence Algorithms Ophthalmology Professional Practice Humans
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Developing and verifying automatic detection of active pulmonary tuberculosis from multi-slice spiral CT images based on deep learning.

Journal of X-ray science and technology Jan 1, 2020
OBJECTIVE: Diagnosis of tuberculosis (TB) in multi-slice spiral computed tomography (CT) images is a difficult task in many TB prevalent locations in which experienced radiologists are lacking. To address this difficulty, we develop an automated dete...
Humans Algorithms Young Adult Adult Male Middle Aged Tomography, X-Ray Computed Female Aged Aged, 80 and over Child, Preschool Child Radiographic Image Interpretation, Computer-Assisted Lung Tuberculosis, Pulmonary Deep Learning Adolescent
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Omics Data and Artificial Intelligence: New Challenges for Gene Therapy.

Current gene therapy Jan 1, 2020
Genome Humans Metagenome Artificial Intelligence Algorithms Transcriptome Proteome Metabolome Genetic Therapy
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Breast Infrared Thermography Segmentation Based on Adaptive Tuning of a Fully Convolutional Network.

Current medical imaging Jan 1, 2020
BACKGROUND: Accurate segmentation of Breast Infrared Thermography is an important step for early detection of breast pathological changes. Automatic segmentation of Breast Infrared Thermography is a very challenging task, as it is difficult to find a...
Neural Networks, Computer Algorithms Female Breast Neoplasms Humans Breast Image Interpretation, Computer-Assisted Thermography
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