AIMC Topic: Machine Learning

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Machine learning methods to improve bedside fluid responsiveness prediction in severe sepsis or septic shock: an observational study.

British journal of anaesthesia
BACKGROUND: Passive leg raising (PLR) predicts fluid responsiveness in critical illness, although restrictions in mobilising patients often preclude this haemodynamic challenge being used. We investigated whether machine learning applied on transthor...

Automatic medical protocol classification using machine learning approaches.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Assignment of medical imaging procedure protocols requires extensive knowledge about patient's data, usually included in radiological request forms and radiological reports. Assignment of protocol is required prior to radiol...

Use of machine learning to identify a T cell response to SARS-CoV-2.

Cell reports. Medicine
The identification of SARS-CoV-2-specific T cell receptor (TCR) sequences is critical for understanding T cell responses to SARS-CoV-2. Accordingly, we reanalyze publicly available data from SARS-CoV-2-recovered patients who had low-severity disease ...

Discrimination of Malaysian stingless bee honey from different entomological origins based on physicochemical properties and volatile compound profiles using chemometrics and machine learning.

Food chemistry
Identification of honey origin based on specific chemical markers is important for honey authentication. This study is aimed to differentiate Malaysian stingless bee honey from different entomological origins (Heterotrigona bakeri, Geniotrigona thora...

A comparison of the value of two machine learning predictive models to support bovine tuberculosis disease control in England.

Preventive veterinary medicine
Nearly a decade into Defra's current eradication strategy, bovine tuberculosis (bTB) remains a serious animal health problem in England, with c.30,000 cattle slaughtered annually in the fight against this insidious disease. There is an urgent need to...

Traffic accident detection and condition analysis based on social networking data.

Accident; analysis and prevention
Accurate detection of traffic accidents as well as condition analysis are essential to effectively restoring traffic flow and reducing serious injuries and fatalities. This goal can be obtained using an advanced data classification model with a rich ...

[Artificial intelligence in cardiology : Relevance, current applications, and future developments].

Herzschrittmachertherapie & Elektrophysiologie
Big data and applications of artificial intelligence (AI), such as machine learning or deep learning, will enrich healthcare in the future and become increasingly important. Among other things, they have the potential to avoid unnecessary examination...

Chemometrics-based models hyphenated with ensemble machine learning for retention time simulation of isoquercitrin in Coriander sativum L. using high-performance liquid chromatography.

Journal of separation science
In this research, two nonlinear models, namely; adaptive neuro-fuzzy inference system and feed-forward neural network and a classical linear model were employed for the prediction of retention time of isoquercitrin in Coriander sativum L. using the h...