AIMC Topic: Probability
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Using the National Trauma Data Bank (NTDB) and machine learning to predict trauma patient mortality at admission.
PloS one
Nov 17, 2020
A 400-estimator gradient boosting classifier was trained to predict survival probabilities of trauma patients. The National Trauma Data Bank (NTDB) provided 799233 complete patient records (778303 survivors and 20930 deaths) each containing 32 featur...
Layer Embedding Analysis in Convolutional Neural Networks for Improved Probability Calibration and Classification.
IEEE transactions on medical imaging
Oct 28, 2020
In this project, our goal is to develop a method for interpreting how a neural network makes layer-by-layer embedded decisions when trained for a classification task, and also to use this insight for improving the model performance. To do this, we fi...
Prediction and analysis of Corona Virus Disease 2019.
PloS one
Oct 5, 2020
The outbreak of Corona Virus Disease 2019 (COVID-19) in Wuhan has significantly impacted the economy and society globally. Countries are in a strict state of prevention and control of this pandemic. In this study, the development trend analysis of th...
A multimodal deep learning-based drug repurposing approach for treatment of COVID-19.
Molecular diversity
Sep 30, 2020
Recently, various computational methods have been proposed to find new therapeutic applications of the existing drugs. The Multimodal Restricted Boltzmann Machine approach (MM-RBM), which has the capability to connect the information about the multip...
Comparison of Scaling Methods to Obtain Calibrated Probabilities of Activity for Protein-Ligand Predictions.
Journal of chemical information and modeling
Sep 21, 2020
In the context of bioactivity prediction, the question of how to calibrate a score produced by a machine learning method into a probability of binding to a protein target is not yet satisfactorily addressed. In this study, we compared the performance...
Fuzzy logic programming and adaptable design of medical products for the COVID-19 anti-epidemic normalization.
Computer methods and programs in biomedicine
Sep 16, 2020
BACKGROUND: The COVID-19 prevention and control constantly affects lives worldwide. In this paper, household medical products were analyzed using fuzzy logic. Considering the household anti-epidemic status, economic and environmental benefits, the ad...
Receiver operating characteristic curves and confidence bands for support vector machines.
Biometrics
Sep 12, 2020
Many problems that appear in biomedical decision-making, such as diagnosing disease and predicting response to treatment, can be expressed as binary classification problems. The support vector machine (SVM) is a popular classification technique that ...
Predicting the frequencies of drug side effects.
Nature communications
Sep 11, 2020
A central issue in drug risk-benefit assessment is identifying frequencies of side effects in humans. Currently, frequencies are experimentally determined in randomised controlled clinical trials. We present a machine learning framework for computati...
Personalized prediction of daily eczema severity scores using a mechanistic machine learning model.
Clinical and experimental allergy : journal of the British Society for Allergy and Clinical Immunology
Sep 9, 2020
BACKGROUND: Atopic dermatitis (AD) is a chronic inflammatory skin disease with periods of flares and remission. Designing personalized treatment strategies for AD is challenging, given the apparent unpredictability and large variation in AD symptoms ...
Dynamic event-based state estimation for delayed artificial neural networks with multiplicative noises: A gain-scheduled approach.
Neural networks : the official journal of the International Neural Network Society
Sep 4, 2020
This study is concerned with the state estimation issue for a kind of delayed artificial neural networks with multiplicative noises. The occurrence of the time delay is in a random way that is modeled by a Bernoulli distributed stochastic variable wh...
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