AIMC Topic: Deep Learning

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Predicting intraoperative bleeding in patients undergoing a hepatectomy using multiple machine learning and deep learning techniques.

Journal of clinical anesthesia Jul 1, 2021
Humans Machine Learning Deep Learning Hemorrhage Hepatectomy
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Review of Statistical Methods for Evaluating the Performance of Survival or Other Time-to-Event Prediction Models (from Conventional to Deep Learning Approaches).

Korean journal of radiology Jul 1, 2021
The recent introduction of various high-dimensional modeling methods, such as radiomics and deep learning, has created a much greater diversity in modeling approaches for survival prediction (or, more generally, time-to-event prediction). The newness...
Humans Deep Learning ROC Curve
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Deep Learning-Based Carotid Plaque Segmentation from B-Mode Ultrasound Images.

Ultrasound in medicine & biology Jul 1, 2021
Carotid ultrasound measurement of total plaque area (TPA) provides a method for quantifying carotid plaque burden and monitoring changes in carotid atherosclerosis in response to medical treatment. Plaque boundary segmentation is required to generate...
Carotid Artery Diseases Carotid Arteries Plaque, Atherosclerotic Humans Deep Learning Ultrasonography
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Deep learning segmentation of transverse musculoskeletal ultrasound images for neuromuscular disease assessment.

Computers in biology and medicine Jul 1, 2021
Ultrasound imaging is a patient-friendly and robust technique for studying physiological and pathological muscles. An automatic deep learning (DL) system for the analysis of ultrasound images could be useful to support an expert operator, allowing th...
Middle Aged Deep Learning Ultrasonography Humans Adult Image Processing, Computer-Assisted Male Algorithms Muscle, Skeletal Aged Neuromuscular Diseases
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Effect of a comprehensive deep-learning model on the accuracy of chest x-ray interpretation by radiologists: a retrospective, multireader multicase study.

The Lancet. Digital health Jul 1, 2021
BACKGROUND: Chest x-rays are widely used in clinical practice; however, interpretation can be hindered by human error and a lack of experienced thoracic radiologists. Deep learning has the potential to improve the accuracy of chest x-ray interpretati...
Radiography, Thoracic Infections X-Rays Radiologists Radiographic Image Interpretation, Computer-Assisted Models, Biological Mass Screening Area Under Curve Humans Artificial Intelligence Thoracic Injuries Retrospective Studies Male Female Middle Aged Adolescent Aged, 80 and over Aged ROC Curve Deep Learning Young Adult Thoracic Neoplasms Adult
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Evaluation of deep learning-based artificial intelligence techniques for breast cancer detection on mammograms: Results from a retrospective study using a BreastScreen Victoria dataset.

Journal of medical imaging and radiation oncology Jul 1, 2021
INTRODUCTION: This study aims to evaluate deep learning (DL)-based artificial intelligence (AI) techniques for detecting the presence of breast cancer on a digital mammogram image.
Humans Prospective Studies Retrospective Studies Deep Learning Mammography Victoria Female Breast Neoplasms
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In silico prediction of chemical-induced hematotoxicity with machine learning and deep learning methods.

Molecular diversity Jul 1, 2021
Chemical-induced hematotoxicity is an important concern in the drug discovery, since it can often be fatal when it happens. It is quite useful for us to give special attention to chemicals which can cause hematotoxicity. In the present study, we focu...
Drug-Related Side Effects and Adverse Reactions Databases, Chemical Blood Cells Humans ROC Curve Machine Learning Models, Molecular Quantitative Structure-Activity Relationship Algorithms Cheminformatics Reproducibility of Results Drug Discovery Deep Learning
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Multi-Task Deep Learning for Real-Time 3D Human Pose Estimation and Action Recognition.

IEEE transactions on pattern analysis and machine intelligence Jul 1, 2021
Human pose estimation and action recognition are related tasks since both problems are strongly dependent on the human body representation and analysis. Nonetheless, most recent methods in the literature handle the two problems separately. In this ar...
Software Algorithms Humans Deep Learning
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Deep Learning Based Prediction on Greenhouse Crop Yield Combined TCN and RNN.

Sensors (Basel, Switzerland) Jul 1, 2021
Currently, greenhouses are widely applied for plant growth, and environmental parameters can also be controlled in the modern greenhouse to guarantee the maximum crop yield. In order to optimally control greenhouses' environmental parameters, one ind...
Algorithms Neural Networks, Computer Machine Learning Deep Learning Agriculture
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Establish a normal fetal lung gestational age grading model and explore the potential value of deep learning algorithms in fetal lung maturity evaluation.

Chinese medical journal Jul 1, 2021
BACKGROUND: Prenatal evaluation of fetal lung maturity (FLM) is a challenge, and an effective non-invasive method for prenatal assessment of FLM is needed. The study aimed to establish a normal fetal lung gestational age (GA) grading model based on d...
Deep Learning Gestational Age Infant, Newborn Infant Humans Lung Pregnancy Neural Networks, Computer Female Algorithms
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