AIMC Topic: Forecasting

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Using Machine Learning Models to Predict In-Hospital Mortality for ST-Elevation Myocardial Infarction Patients.

Studies in health technology and informatics
Acute myocardial infarction is a major cause of hospitalization and mortality in China, where ST-elevation myocardial infarction (STEMI) is more severe and has a higher mortality rate. Accurate and interpretable prediction of in-hospital mortality is...

Standardization of Assistive Products with Robotic Technology - From a Perspective of ISO/TC173.

Studies in health technology and informatics
ISO/TC173 is a technical committee, in charge of international standardization of assistive products (APs). Robotic technology (RT) is currently an important topic in this field. APs with RT will be included in future revisions of the scope of TC173....

AUCpreD: proteome-level protein disorder prediction by AUC-maximized deep convolutional neural fields.

Bioinformatics (Oxford, England)
MOTIVATION: Protein intrinsically disordered regions (IDRs) play an important role in many biological processes. Two key properties of IDRs are (i) the occurrence is proteome-wide and (ii) the ratio of disordered residues is about 6%, which makes it ...

Higher order methylation features for clustering and prediction in epigenomic studies.

Bioinformatics (Oxford, England)
MOTIVATION: DNA methylation is an intensely studied epigenetic mark, yet its functional role is incompletely understood. Attempts to quantitatively associate average DNA methylation to gene expression yield poor correlations outside of the well-under...

Robot chores: machines make the decisions on mock maternity ward.

Nursing standard (Royal College of Nursing (Great Britain) : 1987)
Robots could be used to make decisions on wards, American scientists have claimed.

[Prediction of schistosomiasis infection rates of population based on ARIMA-NARNN model].

Zhongguo xue xi chong bing fang zhi za zhi = Chinese journal of schistosomiasis control
OBJECTIVE: To explore the effect of the autoregressive integrated moving average model-nonlinear auto-regressive neural network (ARIMA-NARNN) model on predicting schistosomiasis infection rates of population.