AI Medical Compendium Topic:
Forecasting

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Robotic Uses in Pediatric Care: A Comprehensive Review.

Journal of pediatric nursing
PROBLEM: Advances in technology have made robotics acceptable in healthcare and medical environments. The aim of this literature review was to examine how the pediatric population can benefit from robotic therapy and assistance that are currently ava...

Progress in Nanorobotics for Advancing Biomedicine.

IEEE transactions on bio-medical engineering
Nanorobotics, which has long been a fantasy in the realm of science fiction, is now a reality due to the considerable developments in diverse fields including chemistry, materials, physics, information and nanotechnology in the past decades. Not only...

Prediction of in-hospital mortality in patients on mechanical ventilation post traumatic brain injury: machine learning approach.

BMC medical informatics and decision making
BACKGROUND: The study aimed to introduce a machine learning model that predicts in-hospital mortality in patients on mechanical ventilation (MV) following moderate to severe traumatic brain injury (TBI).

Predicting hospitalization following psychiatric crisis care using machine learning.

BMC medical informatics and decision making
BACKGROUND: Accurate prediction models for whether patients on the verge of a psychiatric criseis need hospitalization are lacking and machine learning methods may help improve the accuracy of psychiatric hospitalization prediction models. In this pa...

Learning from urban form to predict building heights.

PloS one
Understanding cities as complex systems, sustainable urban planning depends on reliable high-resolution data, for example of the building stock to upscale region-wide retrofit policies. For some cities and regions, these data exist in detailed 3D mod...

Deep Learning for Time Series Forecasting: A Survey.

Big data
Time series forecasting has become a very intensive field of research, which is even increasing in recent years. Deep neural networks have proved to be powerful and are achieving high accuracy in many application fields. For these reasons, they are o...

Time series prediction of under-five mortality rates for Nigeria: comparative analysis of artificial neural networks, Holt-Winters exponential smoothing and autoregressive integrated moving average models.

BMC medical research methodology
BACKGROUND: Accurate forecasting model for under-five mortality rate (U5MR) is essential for policy actions and planning. While studies have used traditional time series modeling techniques (e.g., autoregressive integrated moving average (ARIMA) and ...