AIMC Topic: Probability

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Determination of probability of causative pathogen in infectious keratitis using deep learning algorithm of slit-lamp images.

Scientific reports Nov 22, 2021
Corneal opacities are important causes of blindness, and their major etiology is infectious keratitis. Slit-lamp examinations are commonly used to determine the causative pathogen; however, their diagnostic accuracy is low even for experienced ophtha...
Corneal Opacity Slit Lamp Microscopy Slit Lamp Probability Diagnostic Techniques, Ophthalmological Aged Male Keratitis Middle Aged Deep Learning Ophthalmology Algorithms Female Humans Reproducibility of Results
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Improving random forest predictions in small datasets from two-phase sampling designs.

BMC medical informatics and decision making Nov 22, 2021
BACKGROUND: While random forests are one of the most successful machine learning methods, it is necessary to optimize their performance for use with datasets resulting from a two-phase sampling design with a small number of cases-a common situation i...
Humans Machine Learning Probability Vaccine Efficacy
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Deep learning-based histopathological segmentation for whole slide images of colorectal cancer in a compressed domain.

Scientific reports Nov 18, 2021
Automatic pattern recognition using deep learning techniques has become increasingly important. Unfortunately, due to limited system memory, general preprocessing methods for high-resolution images in the spatial domain can lose important data inform...
Neural Networks, Computer Machine Learning Software Humans Colorectal Neoplasms Deep Learning User-Computer Interface Algorithms Computers Reproducibility of Results Computer Graphics Principal Component Analysis Probability Wavelet Analysis Image Processing, Computer-Assisted Predictive Value of Tests
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Predicting completion of clinical trials in pregnant women: Cox proportional hazard and neural network models.

Clinical and translational science Nov 17, 2021
This study aimed to develop a model for predicting the completion of clinical trials involving pregnant women using the Cox proportional hazard model and neural network model (DeepSurv) and to compare the predictive performance of both methods. We co...
Probability Proportional Hazards Models Humans Neural Networks, Computer Pregnancy Female Pregnant People
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A Novel Occupancy Mapping Framework for Risk-Aware Path Planning in Unstructured Environments.

Sensors (Basel, Switzerland) Nov 14, 2021
In the context of autonomous robots, one of the most important tasks is to prevent potential damage to the robot during navigation. For this purpose, it is often assumed that one must deal with known probabilistic obstacles, then compute the probabil...
Algorithms Robotics Bayes Theorem Probability
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FOREX rate prediction improved by Elliott waves patterns based on neural networks.

Neural networks : the official journal of the International Neural Network Society Nov 5, 2021
Financial market predictions represent a complex problem. Most prediction systems work with the term time window, which is represented by exchange rate values of a real financial commodity. Such values (time window) provide the base for prediction of...
Probability Neural Networks, Computer Forecasting
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Accuracy of deep learning-based computed tomography diagnostic system for COVID-19: A consecutive sampling external validation cohort study.

PloS one Nov 4, 2021
Ali-M3, an artificial intelligence program, analyzes chest computed tomography (CT) and detects the likelihood of coronavirus disease (COVID-19) based on scores ranging from 0 to 1. However, Ali-M3 has not been externally validated. Our aim was to ev...
Diagnosis, Computer-Assisted Probability Deep Learning Female Cohort Studies Reverse Transcriptase Polymerase Chain Reaction Humans Reproducibility of Results Algorithms SARS-CoV-2 Male Retrospective Studies COVID-19 Middle Aged Tomography, X-Ray Computed Aged Adult Sensitivity and Specificity Area Under Curve Japan COVID-19 Testing ROC Curve Image Processing, Computer-Assisted
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Building a predictive model to assist in the diagnosis of cervical cancer.

Future oncology (London, England) Nov 3, 2021
Cervical cancer is still one of the most common gynecologic cancers in the world. Since cervical cancer is a potentially preventive cancer, earlier detection is the most effective technique for decreasing the worldwide incidence of the illness. Thi...
Humans Machine Learning Algorithms Female Logistic Models Uterine Cervical Neoplasms Cross-Sectional Studies Decision Trees Probability
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Epistemic uncertainty quantification in deep learning classification by the Delta method.

Neural networks : the official journal of the International Neural Network Society Oct 23, 2021
The Delta method is a classical procedure for quantifying epistemic uncertainty in statistical models, but its direct application to deep neural networks is prevented by the large number of parameters P. We propose a low cost approximation of the Del...
Uncertainty Deep Learning Models, Statistical Probability Neural Networks, Computer
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On the capacity of deep generative networks for approximating distributions.

Neural networks : the official journal of the International Neural Network Society Oct 21, 2021
We study the efficacy and efficiency of deep generative networks for approximating probability distributions. We prove that neural networks can transform a low-dimensional source distribution to a distribution that is arbitrarily close to a high-dime...
Neural Networks, Computer Probability
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