AIMC Topic: Machine Learning

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The study of automatic machine learning base on radiomics of non-focus area in the first chest CT of different clinical types of COVID-19 pneumonia.

Scientific reports
To explore the possibility of predicting the clinical types of Corona-Virus-Disease-2019 (COVID-19) pneumonia by analyzing the non-focus area of the lung in the first chest CT image of patients with COVID-19 by using automatic machine learning (Auto-...

Classification of Depression Through Resting-State Electroencephalogram as a Novel Practice in Psychiatry: Review.

Journal of medical Internet research
BACKGROUND: Machine learning applications in health care have increased considerably in the recent past, and this review focuses on an important application in psychiatry related to the detection of depression. Since the advent of computational psych...

Interactive Dual Attention Network for Text Sentiment Classification.

Computational intelligence and neuroscience
Text sentiment classification is an essential research field of natural language processing. Recently, numerous deep learning-based methods for sentiment classification have been proposed and achieved better performances compared with conventional ma...

Risk mitigation in algorithmic accountability: The role of machine learning copies.

PloS one
Machine learning plays an increasingly important role in our society and economy and is already having an impact on our daily life in many different ways. From several perspectives, machine learning is seen as the new engine of productivity and econo...

Gradient-based training and pruning of radial basis function networks with an application in materials physics.

Neural networks : the official journal of the International Neural Network Society
Many applications, especially in physics and other sciences, call for easily interpretable and robust machine learning techniques. We propose a fully gradient-based technique for training radial basis function networks with an efficient and scalable ...

Development of a Dynamic Diagnosis Grading System for Infertility Using Machine Learning.

JAMA network open
IMPORTANCE: Many indicators need to be considered when judging the condition of patients with infertility, which makes diagnosis and treatment complicated.

Development, Validation, and Evaluation of a Simple Machine Learning Model to Predict Cirrhosis Mortality.

JAMA network open
IMPORTANCE: Machine-learning algorithms offer better predictive accuracy than traditional prognostic models but are too complex and opaque for clinical use.

Use of machine learning to classify adult ADHD and other conditions based on the Conners' Adult ADHD Rating Scales.

Scientific reports
A reliable diagnosis of adult Attention Deficit/Hyperactivity Disorder (ADHD) is challenging as many of the symptoms of ADHD resemble symptoms of other disorders. ADHD is associated with gambling disorder and obesity, showing overlaps of about 20% wi...