AI Medical Compendium Topic

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Statistics, Nonparametric

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Tree-Based Learning of Regulatory Network Topologies and Dynamics with Jump3.

Methods in molecular biology (Clifton, N.J.)
Inference of gene regulatory networks (GRNs) from time series data is a well-established field in computational systems biology. Most approaches can be broadly divided in two families: model-based and model-free methods. These two families are highly...

Comparison of Deep Learning Approaches for Multi-Label Chest X-Ray Classification.

Scientific reports
The increased availability of labeled X-ray image archives (e.g. ChestX-ray14 dataset) has triggered a growing interest in deep learning techniques. To provide better insight into the different approaches, and their applications to chest X-ray classi...

Evolving neural networks to follow trajectories of arbitrary complexity.

Neural networks : the official journal of the International Neural Network Society
Many experiments have been performed that use evolutionary algorithms for learning the topology and connection weights of a neural network that controls a robot or virtual agent. These experiments are not only performed to better understand basic bio...

Machine Learning Approaches for Automated Lesion Detection in Microwave Breast Imaging Clinical Data.

Scientific reports
Breast lesion detection employing state of the art microwave systems provide a safe, non-ionizing technique that can differentiate healthy and non-healthy tissues by exploiting their dielectric properties. In this paper, a microwave apparatus for bre...

Variable Selection for Nonparametric Learning with Power Series Kernels.

Neural computation
In this letter, we propose a variable selection method for general nonparametric kernel-based estimation. The proposed method consists of two-stage estimation: (1) construct a consistent estimator of the target function, and (2) approximate the estim...

Evaluation of an AI-based, automatic coronary artery calcium scoring software.

European radiology
OBJECTIVES: To evaluate an artificial intelligence (AI)-based, automatic coronary artery calcium (CAC) scoring software, using a semi-automatic software as a reference.

Guided neural style transfer for shape stylization.

PloS one
Designing logos, typefaces, and other decorated shapes can require professional skills. In this paper, we aim to produce new and unique decorated shapes by stylizing ordinary shapes with machine learning. Specifically, we combined parametric and non-...

Machine learning-based mortality rate prediction using optimized hyper-parameter.

Computer methods and programs in biomedicine
OBJECTIVE AND BACKGROUND: The current scenario of the Pandemic of COVID-19 demands multi-channel investigations and predictions. A variety of prediction models are available in the literature. The majority of these models are based on extrapolating b...

A robust algorithm for explaining unreliable machine learning survival models using the Kolmogorov-Smirnov bounds.

Neural networks : the official journal of the International Neural Network Society
A new robust algorithm based on the explanation method SurvLIME called SurvLIME-KS is proposed for explaining machine learning survival models. The algorithm is developed to ensure robustness to cases of a small amount of training data or outliers of...

Using Auto-Segmentation to Reduce Contouring and Dose Inconsistency in Clinical Trials: The Simulated Impact on RTOG 0617.

International journal of radiation oncology, biology, physics
PURPOSE: Contouring inconsistencies are known but understudied in clinical radiation therapy trials. We applied auto-contouring to the Radiation Therapy Oncology Group (RTOG) 0617 dose escalation trial data. We hypothesized that the trial heart doses...