AIMC Topic: Sensitivity and Specificity
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Novel computer algorithm for cough monitoring based on octonions.
Respiratory physiology & neurobiology
Mar 27, 2018
The objective assessment of cough frequency is essential for evaluation of cough and antitussive therapies. Nonetheless, available algorithms for automatic detection of cough sound have limited sensitivity and the analysis of cough sound often requir...
Deep learning in mammography and breast histology, an overview and future trends.
Medical image analysis
Mar 26, 2018
Recent improvements in biomedical image analysis using deep learning based neural networks could be exploited to enhance the performance of Computer Aided Diagnosis (CAD) systems. Considering the importance of breast cancer worldwide and the promisin...
Classification of Alzheimer's Disease Based on Eight-Layer Convolutional Neural Network with Leaky Rectified Linear Unit and Max Pooling.
Journal of medical systems
Mar 26, 2018
Alzheimer's disease (AD) is a progressive brain disease. The goal of this study is to provide a new computer-vision based technique to detect it in an efficient way. The brain-imaging data of 98 AD patients and 98 healthy controls was collected using...
Detecting oropharyngeal carcinoma using multispectral, narrow-band imaging and machine learning.
The Laryngoscope
Mar 25, 2018
OBJECTIVE: To determine if multispectral narrow-band imaging (mNBI) can be used for automated, quantitative detection of oropharyngeal carcinoma (OPC).
Deep feature classification of angiomyolipoma without visible fat and renal cell carcinoma in abdominal contrast-enhanced CT images with texture image patches and hand-crafted feature concatenation.
Medical physics
Mar 25, 2018
PURPOSE: To develop an automatic deep feature classification (DFC) method for distinguishing benign angiomyolipoma without visible fat (AMLwvf) from malignant clear cell renal cell carcinoma (ccRCC) from abdominal contrast-enhanced computer tomograph...
Model-Based Feature Augmentation for Cardiac Ablation Target Learning From Images.
IEEE transactions on bio-medical engineering
Mar 22, 2018
GOAL: We present a model-based feature augmentation scheme to improve the performance of a learning algorithm for the detection of cardiac radio-frequency ablation (RFA) targets with respect to learning from images alone.
A novel feature extraction technique for pulmonary sound analysis based on EMD.
Computer methods and programs in biomedicine
Mar 22, 2018
BACKGROUND AND OBJECTIVE: The stethoscope based auscultation technique is a primary diagnostic tool for chest sound analysis. However, the performance of this method is limited due to its dependency on physicians experience, knowledge and also clarit...
Predicting Treatment Response to Intra-arterial Therapies for Hepatocellular Carcinoma with the Use of Supervised Machine Learning-An Artificial Intelligence Concept.
Journal of vascular and interventional radiology : JVIR
Mar 14, 2018
PURPOSE: To use magnetic resonance (MR) imaging and clinical patient data to create an artificial intelligence (AI) framework for the prediction of therapeutic outcomes of transarterial chemoembolization by applying machine learning (ML) techniques.
Chemoembolization, Therapeutic
Ethiodized Oil
Sensitivity and Specificity
Male
Magnetic Resonance Imaging
Middle Aged
Predictive Value of Tests
Antineoplastic Agents
Neoplasm Staging
Retrospective Studies
Humans
Liver Neoplasms
Doxorubicin
Machine Learning
Carcinoma, Hepatocellular
Female
Treatment Outcome
Aged
Contrast Media
Adult
Predicting urinary tract infections in the emergency department with machine learning.
PloS one
Mar 7, 2018
BACKGROUND: Urinary tract infection (UTI) is a common emergency department (ED) diagnosis with reported high diagnostic error rates. Because a urine culture, part of the gold standard for diagnosis of UTI, is usually not available for 24-48 hours aft...
Acral melanoma detection using a convolutional neural network for dermoscopy images.
PloS one
Mar 7, 2018
BACKGROUND/PURPOSE: Acral melanoma is the most common type of melanoma in Asians, and usually results in a poor prognosis due to late diagnosis. We applied a convolutional neural network to dermoscopy images of acral melanoma and benign nevi on the h...
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