AIMC Topic: Machine Learning

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Early Warning of Gas Concentration in Coal Mines Production Based on Probability Density Machine.

Sensors (Basel, Switzerland)
Gas explosion has always been an important factor restricting coal mine production safety. The application of machine learning techniques in coal mine gas concentration prediction and early warning can effectively prevent gas explosion accidents. Nea...

Machine learning model to predict hypotension after starting continuous renal replacement therapy.

Scientific reports
Hypotension after starting continuous renal replacement therapy (CRRT) is associated with worse outcomes compared with normotension, but it is difficult to predict because several factors have interactive and complex effects on the risk. The present ...

Machine Learning of Bacterial Transcriptomes Reveals Responses Underlying Differential Antibiotic Susceptibility.

mSphere
antibiotic susceptibility testing often fails to accurately predict drug efficacies, in part due to differences in the molecular composition between standardized bacteriologic media and physiological environments within the body. Here, we investiga...

Assigning function to SNPs: Considerations when interpreting genetic variation.

Seminars in cell & developmental biology
Assigning function to single nucleotide polymorphisms (SNPs) to understand the mechanisms that link genetic and phenotypic variation and disease is an area of intensive research that is necessary to contribute to the continuing development of precisi...

Machine Learning and Chemical Imaging to Elucidate Enzyme Immobilization for Biocatalysis.

Analytical chemistry
Biocatalysis has rapidly become an essential tool in the scientific and industrial communities for the development of efficient, safe, and sustainable chemical syntheses. Immobilization of the biocatalyst, typically an engineered enzyme, offers signi...

Dengue models based on machine learning techniques: A systematic literature review.

Artificial intelligence in medicine
BACKGROUND: Dengue modeling is a research topic that has increased in recent years. Early prediction and decision-making are key factors to control dengue. This Systematic Literature Review (SLR) analyzes three modeling approaches of dengue: diagnost...

Applications of machine learning to undifferentiated chest pain in the emergency department: A systematic review.

PloS one
BACKGROUND: Chest pain is amongst the most common reason for presentation to the emergency department (ED). There are many causes of chest pain, and it is important for the emergency physician to quickly and accurately diagnose life threatening cause...

Development of a machine learning-based real-time location system to streamline acute endovascular intervention in acute stroke: a proof-of-concept study.

Journal of neurointerventional surgery
BACKGROUND: Delivery of acute stroke endovascular intervention can be challenging because it requires complex coordination of patient and staff across many different locations. In this proof-of-concept paper we (a) examine whether WiFi fingerprinting...

Atomic Structure-Free Representation of Active Motifs for Expedited Catalyst Discovery.

Journal of chemical information and modeling
To discover new catalysts using density functional theory (DFT) calculations, binding energies of reaction intermediates are considered as descriptors to predict catalytic activities. Recently, machine learning methods have been developed to reduce t...

Assessment of Volatile Aromatic Compounds in Smoke Tainted Cabernet Sauvignon Wines Using a Low-Cost E-Nose and Machine Learning Modelling.

Molecules (Basel, Switzerland)
Wine aroma is an important quality trait in wine, influenced by its volatile compounds. Many factors can affect the composition and levels (concentration) of volatile aromatic compounds, including the water status of grapevines, canopy management, an...