AIMC Topic: Humans

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KecNet: A Light Neural Network for Arrhythmia Classification Based on Knowledge Reinforcement.

Journal of healthcare engineering Apr 24, 2021
Acquiring electrocardiographic (ECG) signals and performing arrhythmia classification in mobile device scenarios have the advantages of short response time, almost no network bandwidth consumption, and human resource savings. In recent years, deep ne...
Arrhythmias, Cardiac Computers, Handheld Algorithms Humans Electrocardiography Neural Networks, Computer Signal Processing, Computer-Assisted
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Machine Learning and Intelligent Diagnostics in Dental and Orofacial Pain Management: A Systematic Review.

Pain research & management Apr 24, 2021
PURPOSE: The study explored the clinical influence, effectiveness, limitations, and human comparison outcomes of machine learning in diagnosing (1) dental diseases, (2) periodontal diseases, (3) trauma and neuralgias, (4) cysts and tumors, (5) glandu...
Facial Pain Pain Management Diagnostic Tests, Routine Artificial Intelligence Machine Learning Algorithms Humans
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Cancer Classification with a Cost-Sensitive Naive Bayes Stacking Ensemble.

Computational and mathematical methods in medicine Apr 24, 2021
Ensemble learning combines multiple learners to perform combinatorial learning, which has advantages of good flexibility and higher generalization performance. To achieve higher quality cancer classification, in this study, the fast correlation-based...
Oligonucleotide Array Sequence Analysis Oncogenes Humans Databases, Genetic Neural Networks, Computer Decision Trees Machine Learning Bayes Theorem Neoplasms Gene Expression Regulation, Neoplastic Algorithms ROC Curve Support Vector Machine Female Computational Biology Male
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Machine Learning with F-Sodium Fluoride PET and Quantitative Plaque Analysis on CT Angiography for the Future Risk of Myocardial Infarction.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine Apr 23, 2021
Coronary F-sodium fluoride (F-NaF) PET and CT angiography-based quantitative plaque analysis have shown promise in refining risk stratification in patients with coronary artery disease. We combined both of these novel imaging approaches to develop an...
Humans Machine Learning Female Image Processing, Computer-Assisted Positron Emission Tomography Computed Tomography Coronary Artery Disease Aged Male Middle Aged Sodium Fluoride Computed Tomography Angiography Myocardial Infarction Fluorine Radioisotopes Plaque, Atherosclerotic
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Applying Contemporary Machine Learning Approaches to Nutrition Care Real-World Evidence: Findings From the National Quality Improvement Data Set.

Journal of the Academy of Nutrition and Dietetics Apr 23, 2021
Using real-world data from the Academy of Nutrition and Dietetics Health Informatics Infrastructure, we use state-of-the-art clustering techniques to identify 2 phenotypes characterizing the episodes of nutrition care observed in the National Quality...
Humans Machine Learning Quality Improvement Datasets as Topic Episode of Care Medical Informatics Dietetics Academies and Institutes
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Deep Learning Estimation of 10-2 and 24-2 Visual Field Metrics Based on Thickness Maps from Macula OCT.

Ophthalmology Apr 23, 2021
PURPOSE: To develop deep learning (DL) systems estimating visual function from macula-centered spectral-domain (SD) OCT images.
Macula Lutea Tomography, Optical Coherence Benchmarking Visual Fields Deep Learning Follow-Up Studies Female Aged Cross-Sectional Studies Intraocular Pressure Male Middle Aged Humans Glaucoma
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Sinogram-based deep learning image reconstruction technique in abdominal CT: image quality considerations.

European radiology Apr 23, 2021
OBJECTIVES: To investigate the image quality and perception of a sinogram-based deep learning image reconstruction (DLIR) algorithm for single-energy abdominal CT compared to standard-of-care strength of ASIR-V.
Image Processing, Computer-Assisted Radiographic Image Interpretation, Computer-Assisted Radiation Dosage Humans Algorithms Retrospective Studies Tomography, X-Ray Computed Deep Learning
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Image Quality Assessment of Fetal Brain MRI Using Multi-Instance Deep Learning Methods.

Journal of magnetic resonance imaging : JMRI Apr 23, 2021
BACKGROUND: Due to random motion of fetuses and maternal respirations, image quality of fetal brain MRIs varies considerably. To address this issue, visual inspection of the images is performed during acquisition phase and after 3D-reconstruction, an...
Brain Retrospective Studies Deep Learning Magnetic Resonance Imaging Fetus Humans
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Deep Learning-Based Denoising in High-Speed Portable Reflectance Confocal Microscopy.

Lasers in surgery and medicine Apr 23, 2021
BACKGROUND AND OBJECTIVE: Portable confocal microscopy (PCM) is a low-cost reflectance confocal microscopy technique that can visualize cellular details of human skin in vivo. When PCM images are acquired with a short exposure time to reduce motion b...
Microscopy, Confocal Signal-To-Noise Ratio Humans Algorithms Deep Learning Image Processing, Computer-Assisted
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Senhance surgical system in benign hysterectomy: A real-world comparative assessment of case times and instrument costs versus da Vinci robotics and laparoscopic-assisted vaginal hysterectomy procedures.

The international journal of medical robotics + computer assisted surgery : MRCAS Apr 23, 2021
OBJECTIVES: Comparison of retrospective, learning curve benign hysterectomy cost and case time data from Senhance total laparoscopic hysterectomy (TLH) cases with similar da Vinci robot cases and laparoscopic-assisted vaginal hysterectomy (LAVH) case...
Humans Laparoscopy Retrospective Studies Hysterectomy Female Hysterectomy, Vaginal Robotics
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