AI Medical Compendium Topic:
Forecasting

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Interpretable time-aware and co-occurrence-aware network for medical prediction.

BMC medical informatics and decision making
BACKGROUND: Disease prediction based on electronic health records (EHRs) is essential for personalized healthcare. But it's hard due to the special data structure and the interpretability requirement of methods. The structure of EHR is hierarchical: ...

A Natural Language Processing-Based Approach for Identifying Hospitalizations for Worsening Heart Failure Within an Integrated Health Care Delivery System.

JAMA network open
IMPORTANCE: The current understanding of epidemiological mechanisms and temporal trends in hospitalizations for worsening heart failure (WHF) is based on claims and national reporting databases. However, these data sources are inherently limited by t...

Estimating the COVID-19 prevalence and mortality using a novel data-driven hybrid model based on ensemble empirical mode decomposition.

Scientific reports
In this study, we proposed a new data-driven hybrid technique by integrating an ensemble empirical mode decomposition (EEMD), an autoregressive integrated moving average (ARIMA), with a nonlinear autoregressive artificial neural network (NARANN), cal...

Application of Improved LSTM Algorithm in Macroeconomic Forecasting.

Computational intelligence and neuroscience
From a macro perspective, futures index of agricultural products can reflect the trend of macroeconomy and can also have an early warning effect on the possible crisis and provide a reference for the government's economic forecast and macro control. ...

Machine learning in the prediction of medical inpatient length of stay.

Internal medicine journal
Length of stay (LOS) estimates are important for patients, doctors and hospital administrators. However, making accurate estimates of LOS can be difficult for medical patients. This review was conducted with the aim of identifying and assessing previ...

Current applications of artificial intelligence in vascular surgery.

Seminars in vascular surgery
Basic foundations of artificial intelligence (AI) include analyzing large amounts of data, recognizing patterns, and predicting outcomes. At the core of AI are well-defined areas, such as machine learning, natural language processing, artificial neur...

A Shape-Constrained Neural Data Fusion Network for Health Index Construction and Residual Life Prediction.

IEEE transactions on neural networks and learning systems
With the rapid development of sensor technologies, multisensor signals are now readily available for health condition monitoring and remaining useful life (RUL) prediction. To fully utilize these signals for a better health condition assessment and R...

Energy Load Forecasting Using a Dual-Stage Attention-Based Recurrent Neural Network.

Sensors (Basel, Switzerland)
Providing a stable, low-price, and safe supply of energy to end-users is a challenging task. The energy service providers are affected by several events such as weather, volatility, and special events. As such, the prediction of these events and havi...

The Short-Term Load Forecasting Using an Artificial Neural Network Approach with Periodic and Nonperiodic Factors: A Case Study of Tai'an, Shandong Province, China.

Computational intelligence and neuroscience
Accurate electricity load forecasting is an important prerequisite for stable electricity system operation. In this paper, it is found that daily and weekly variations are prominent by the power spectrum analysis of the historical loads collected hou...

Intelligent Techniques for Detecting Network Attacks: Review and Research Directions.

Sensors (Basel, Switzerland)
The significant growth in the use of the Internet and the rapid development of network technologies are associated with an increased risk of network attacks. Network attacks refer to all types of unauthorized access to a network including any attempt...