AIMC Topic: Machine Learning

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The Use of Emotional Artificial Intelligence in Plastic Surgery.

Plastic and reconstructive surgery
BACKGROUND: The use of social media to discuss topics related to and within plastic surgery has become widespread in recent years; however, it remains unclear how to use this abundance of largely untapped data to propagate educational research in the...

Uncovering the mouse olfactory long non-coding transcriptome with a novel machine-learning model.

DNA research : an international journal for rapid publication of reports on genes and genomes
Very little is known about long non-coding RNAs (lncRNAs) in the mammalian olfactory sensory epithelia. Deciphering the non-coding transcriptome in olfaction is relevant because these RNAs have been shown to play a role in chromatin modification and ...

Toward Complete Structured Information Extraction from Radiology Reports Using Machine Learning.

Journal of digital imaging
Unstructured and semi-structured radiology reports represent an underutilized trove of information for machine learning (ML)-based clinical informatics applications, including abnormality tracking systems, research cohort identification, point-of-car...

Deep-Learning-Based Semantic Labeling for 2D Mammography and Comparison of Complexity for Machine Learning Tasks.

Journal of digital imaging
Machine learning has several potential uses in medical imaging for semantic labeling of images to improve radiologist workflow and to triage studies for review. The purpose of this study was to (1) develop deep convolutional neural networks (DCNNs) f...

Using Smartphone Survey Data and Machine Learning to Identify Situational and Contextual Risk Factors for HIV Risk Behavior Among Men Who Have Sex with Men Who Are Not on PrEP.

Prevention science : the official journal of the Society for Prevention Research
"Just-in-time" interventions (JITs) delivered via smartphones have considerable potential for reducing HIV risk behavior by providing pivotal support at key times prior to sex. However, these programs depend on a thorough understanding of when risk b...

Outlier detection for questionnaire data in biobanks.

International journal of epidemiology
BACKGROUND: Biobanks increasingly collect, process and store omics with more conventional epidemiologic information necessitating considerable effort in data cleaning. An efficient outlier detection method that reduces manual labour is highly desirab...

Breast Cancer Classification from Histopathological Images with Inception Recurrent Residual Convolutional Neural Network.

Journal of digital imaging
The Deep Convolutional Neural Network (DCNN) is one of the most powerful and successful deep learning approaches. DCNNs have already provided superior performance in different modalities of medical imaging including breast cancer classification, segm...

Utility of machine learning algorithms in assessing patients with a systemic right ventricle.

European heart journal. Cardiovascular Imaging
AIMS: To investigate the utility of novel deep learning (DL) algorithms in recognizing transposition of the great arteries (TGA) after atrial switch procedure or congenitally corrected TGA (ccTGA) based on routine transthoracic echocardiograms. In ad...