AIMC Topic: Forecasting

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EPTs-TL: A two-level approach for efficient event prediction in healthcare.

Artificial intelligence in medicine
Recently, the event prediction on time series (EPTs) was discussed as one of the important and interesting research trends that its usage is growing for taking proper decisions in the various sciences. In the real-world, time series event-based analy...

Predicted Cellular Immunity Population Coverage Gaps for SARS-CoV-2 Subunit Vaccines and Their Augmentation by Compact Peptide Sets.

Cell systems
Subunit vaccines induce immunity to a pathogen by presenting a component of the pathogen and thus inherently limit the representation of pathogen peptides for cellular immunity-based memory. We find that severe acute respiratory syndrome coronavirus ...

Do clinical and paraclinical findings have the power to predict critical conditions of injured patients after traumatic injury resuscitation? Using data mining artificial intelligence.

Chinese journal of traumatology = Zhonghua chuang shang za zhi
PURPOSE: The triage and initial care of injured patients and a subsequent right level of care is paramount for an overall outcome after traumatic injury. Early recognition of patients is an important case of such decision-making with risk of worse pr...

Machine learning to predict early TNF inhibitor users in patients with ankylosing spondylitis.

Scientific reports
We aim to generate an artificial neural network (ANN) model to predict early TNF inhibitor users in patients with ankylosing spondylitis. The baseline demographic and laboratory data of patients who visited Samsung Medical Center rheumatology clinic ...

Crash narrative classification: Identifying agricultural crashes using machine learning with curated keywords.

Traffic injury prevention
OBJECTIVE: Traditionally, structured or coded data fields from a crash report are the basis for identifying crashes involving different types of vehicles, such as farm equipment. However, using only the structured data can lead to misclassification o...

Prediction of hierarchical time series using structured regularization and its application to artificial neural networks.

PloS one
This paper discusses the prediction of hierarchical time series, where each upper-level time series is calculated by summing appropriate lower-level time series. Forecasts for such hierarchical time series should be coherent, meaning that the forecas...

Modeling and predicting vehicle accident occurrence in Chattanooga, Tennessee.

Accident; analysis and prevention
Given the ever present threat of vehicular accident occurrence endangering the lives of most people, preventative measures need to be taken to combat vehicle accident occurrence. From dangerous weather to hazardous roadway conditions, there are a hig...

Evaluation of classification and forecasting methods on time series gene expression data.

PloS one
Time series gene expression data is widely used to study different dynamic biological processes. Although gene expression datasets share many of the characteristics of time series data from other domains, most of the analyses in this field do not ful...