AIMC Topic: Humans

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Application of deep learning to improve sleep scoring of wrist actigraphy.

Sleep medicine
BACKGROUND: Estimation of sleep parameters by wrist actigraphy is highly dependent on performance of the interpretative algorithm (IA) that converts movement data into sleep/wake scores.

Machine learning algorithms for predicting malnutrition among under-five children in Bangladesh.

Nutrition (Burbank, Los Angeles County, Calif.)
OBJECTIVE: The aim of this study was is to predict malnutrition status in under-five children in Bangladesh by using various machine learning (ML) algorithms.

Automated detection and classification of shoulder arthroplasty models using deep learning.

Skeletal radiology
OBJECTIVE: To develop and evaluate the performance of deep convolutional neural networks (DCNN) to detect and identify specific total shoulder arthroplasty (TSA) models.

Common cancer biomarkers of breast and ovarian types identified through artificial intelligence.

Chemical biology & drug design
Biomarkers can offer great promise for improving prevention and treatment of complex diseases such as cancer, cardiovascular diseases, and diabetes. These can be used as either diagnostic or predictive or as prognostic biomarkers. The revolution brou...

Impulsive synchronization of coupled delayed neural networks with actuator saturation and its application to image encryption.

Neural networks : the official journal of the International Neural Network Society
The actuator of any physical control systems is constrained by amplitude and energy, which causes the control systems to be inevitably affected by actuator saturation. In this paper, impulsive synchronization of coupled delayed neural networks with a...

Artificial intelligence approach fighting COVID-19 with repurposing drugs.

Biomedical journal
BACKGROUND: The ongoing COVID-19 pandemic has caused more than 193,825 deaths during the past few months. A quick-to-be-identified cure for the disease will be a therapeutic medicine that has prior use experiences in patients in order to resolve the ...

Learning from irregularly sampled data for endomicroscopy super-resolution: a comparative study of sparse and dense approaches.

International journal of computer assisted radiology and surgery
PURPOSE: Probe-based confocal laser endomicroscopy (pCLE) enables performing an optical biopsy via a probe. pCLE probes consist of multiple optical fibres arranged in a bundle, which taken together generate signals in an irregularly sampled pattern. ...

Quantitative Prediction of Hemolytic Toxicity for Small Molecules and Their Potential Hemolytic Fragments by Machine Learning and Recursive Fragmentation Methods.

Journal of chemical information and modeling
Hemolytic toxicity, as one of the key toxicity endpoints for small molecules, can cause lysis of the erythrocyte membrane and subsequent release of hemoglobin into blood plasma, leading to multiple acute and chronic adverse effects. Hence, it is nece...

Deep learning in generating radiology reports: A survey.

Artificial intelligence in medicine
Substantial progress has been made towards implementing automated radiology reporting models based on deep learning (DL). This is due to the introduction of large medical text/image datasets. Generating radiology coherent paragraphs that do more than...