AI Medical Compendium Topic:
Forecasting

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Vehicle trajectory prediction and generation using LSTM models and GANs.

PloS one
Vehicles' trajectory prediction is a topic with growing interest in recent years, as there are applications in several domains ranging from autonomous driving to traffic congestion prediction and urban planning. Predicting trajectories starting from ...

Assessing the utility of deep neural networks in predicting postoperative surgical complications: a retrospective study.

The Lancet. Digital health
BACKGROUND: Early detection of postoperative complications, including organ failure, is pivotal in the initiation of targeted treatment strategies aimed at attenuating organ damage. In an era of increasing health-care costs and limited financial reso...

Deep LSTM-Based Transfer Learning Approach for Coherent Forecasts in Hierarchical Time Series.

Sensors (Basel, Switzerland)
Hierarchical time series is a set of data sequences organized by aggregation constraints to represent many real-world applications in research and the industry. Forecasting of hierarchical time series is a challenging and time-consuming problem owing...

Automation in radiotherapy treatment planning: Examples of use in clinical practice and future trends for a complete automated workflow.

Cancer radiotherapie : journal de la Societe francaise de radiotherapie oncologique
Modern radiotherapy treatment planning is a complex and time-consuming process that requires the skills of experienced users to obtain quality plans. Since the early 2000s, the automation of this planning process has become an important research topi...

A Synchronous Prediction Model Based on Multi-Channel CNN with Moving Window for Coal and Electricity Consumption in Cement Calcination Process.

Sensors (Basel, Switzerland)
The precision and reliability of the synchronous prediction of multi energy consumption indicators such as electricity and coal consumption are important for the production optimization of industrial processes (e.g., in the cement industry) due to th...

Impact of chart image characteristics on stock price prediction with a convolutional neural network.

PloS one
Stock price prediction has long been the subject of research because of the importance of accuracy of prediction and the difficulty in forecasting. Traditionally, forecasting has involved linear models such as AR and MR or nonlinear models such as AN...

Artificial Intelligence Techniques: Analysis, Application, and Outcome in Dentistry-A Systematic Review.

BioMed research international
OBJECTIVE: The objective of this systematic review was to investigate the quality and outcome of studies into artificial intelligence techniques, analysis, and effect in dentistry.

Analysis of Enterprise Human Resources Demand Forecast Model Based on SOM Neural Network.

Computational intelligence and neuroscience
Human resource planning is the prerequisite of human resource management, and the basic work of human resource planning is to predict human resource demand. Scientific and reasonable human resource demand forecasting results can provide important dat...

Prediction and Early Warning of Regional Coordinated Development Based on Convolution Neural Network Algorithm.

Computational intelligence and neuroscience
In order to respond to the regional coordinated development of the country, it is necessary to put forward a method that can predict and analyze the development trend according to the current development situation. In view of this, the research will ...

Robotic Applications in Orthodontics: Changing the Face of Contemporary Clinical Care.

BioMed research international
The last decade (2010-2021) has witnessed the evolution of robotic applications in orthodontics. This review scopes and analyzes published orthodontic literature in eight different domains: (1) robotic dental assistants; (2) robotics in diagnosis and...