AIMC Topic: Machine Learning

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Anomaly Detection Using Autoencoder Reconstruction upon Industrial Motors.

Sensors (Basel, Switzerland)
Rotary machine breakdown detection systems are outdated and dependent upon routine testing to discover faults. This is costly and often reactive in nature. Real-time monitoring offers a solution for detecting faults without the need for manual observ...

Prospects and Pitfalls of Machine Learning in Nutritional Epidemiology.

Nutrients
Nutritional epidemiology employs observational data to discover associations between diet and disease risk. However, existing analytic methods of dietary data are often sub-optimal, with limited incorporation and analysis of the correlations between ...

One Cell At a Time (OCAT): a unified framework to integrate and analyze single-cell RNA-seq data.

Genome biology
Integrative analysis of large-scale single-cell RNA sequencing (scRNA-seq) datasets can aggregate complementary biological information from different datasets. However, most existing methods fail to efficiently integrate multiple large-scale scRNA-se...

IAT faking indices revisited: Aspects of replicability and differential validity.

Behavior research methods
Research demonstrates that IATs are fakeable. Several indices [either slowing down or speeding up, and increasing errors or reducing errors in congruent and incongruent blocks; Combined Task Slowing (CTS); Ratio 150-10000] have been developed to dete...

Closing the Control Loop with Time-Variant Embedded Soft Sensors and Recurrent Neural Networks.

Soft robotics
Embedded soft sensors can significantly impact the design and control of soft-bodied robots. Although there have been considerable advances in technology behind these novel sensing materials, their application in real-world tasks, especially in close...

The Need for Medical Artificial Intelligence That Incorporates Prior Images.

Radiology
The use of artificial intelligence (AI) has grown dramatically in the past few years in the United States and worldwide, with more than 300 AI-enabled devices approved by the U.S. Food and Drug Administration (FDA). Most of these AI-enabled applicati...

A method to classify bone marrow cells with rejected option.

Biomedizinische Technik. Biomedical engineering
Bone marrow cell morphology has always been an important tool for the diagnosis of blood diseases. Still, it requires years of experience from a suitable person. Furthermore, the outcomes of their recognition are subjective and there is no objective ...

Clinical Machine Learning Modeling Studies: Methodology and Data Reporting.

Journal of neuro-ophthalmology : the official journal of the North American Neuro-Ophthalmology Society

Machine learning in evolutionary studies comes of age.

Proceedings of the National Academy of Sciences of the United States of America

Effects of Multi-Omics Characteristics on Identification of Driver Genes Using Machine Learning Algorithms.

Genes
Cancer is a complex disease caused by genomic and epigenetic alterations; hence, identifying meaningful cancer drivers is an important and challenging task. Most studies have detected cancer drivers with mutated traits, while few studies consider mul...