AIMC Topic: Machine Learning

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Ultrastretchable Segmented Sensors for Functional Human-Machine Interfaces.

ACS applied materials & interfaces
The key feature that enables soft sensors to shorten the performance gap between robots and biological structures is their deformability, coupled with their capability to measure physical changes. Robots equipped with these sensors can interact safel...

Rapid, antibiotic incubation-free determination of tuberculosis drug resistance using machine learning and Raman spectroscopy.

Proceedings of the National Academy of Sciences of the United States of America
Tuberculosis (TB) is the world's deadliest infectious disease, with over 1.5 million deaths and 10 million new cases reported anually. The causative organism (Mtb) can take nearly 40 d to culture, a required step to determine the pathogen's antibiot...

A Systematic Review of Genetics- and Molecular-Pathway-Based Machine Learning Models for Neurological Disorder Diagnosis.

International journal of molecular sciences
The process of identification and management of neurological disorder conditions faces challenges, prompting the investigation of novel methods in order to improve diagnostic accuracy. In this study, we conducted a systematic literature review to ide...

Machine learning integrative approaches to advance computational immunology.

Genome medicine
The study of immunology, traditionally reliant on proteomics to evaluate individual immune cells, has been revolutionized by single-cell RNA sequencing. Computational immunologists play a crucial role in analysing these datasets, moving beyond tradit...

Evaluation of machine learning approach for surgical results of Ahmed valve implantation in patients with glaucoma.

BMC ophthalmology
BACKGROUND: Ahmed valve implantation demonstrated an increasing proportion in glaucoma surgery, but predicting the successful maintenance of target intraocular pressure remains a challenging task. This study aimed to evaluate the performance of machi...

Utilization of machine learning for dengue case screening.

BMC public health
Dengue causes approximately 10.000 deaths and 100 million symptomatic infections annually worldwide, making it a significant public health concern. To address this, artificial intelligence tools like machine learning can play a crucial role in develo...

Development and validation of a machine learning-based readmission risk prediction model for non-ST elevation myocardial infarction patients after percutaneous coronary intervention.

Scientific reports
To investigate the factors that influence readmissions in patients with acute non-ST elevation myocardial infarction (NSTEMI) after percutaneous coronary intervention (PCI) by using multiple machine learning (ML) methods to establish a predictive mod...

Near-field microwave sensing technology enhanced with machine learning for the non-destructive evaluation of packaged food and beverage products.

Scientific reports
In the food industry, the increasing use of automatic processes in the production line is contributing to the higher probability of finding contaminants inside food packages. Detecting these contaminants before sending the products to market has beco...

A machine learning framework for spatio-temporal vulnerability mapping of groundwaters to nitrate in a data scarce region in Lenjanat Plain, Iran.

Environmental science and pollution research international
The temporal aspect of groundwater vulnerability to contaminants such as nitrate is often overlooked, assuming vulnerability has a static nature. This study bridges this gap by employing machine learning with Detecting Breakpoints and Estimating Segm...