AI Medical Compendium Topic:
Forecasting

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[Artificial intelligence in cardiology : Relevance, current applications, and future developments].

Herzschrittmachertherapie & Elektrophysiologie
Big data and applications of artificial intelligence (AI), such as machine learning or deep learning, will enrich healthcare in the future and become increasingly important. Among other things, they have the potential to avoid unnecessary examination...

The history of robotic surgery and its evolution: when illusion becomes reality.

Revista do Colegio Brasileiro de Cirurgioes
The term "robot" was concepted in the beginning of last century, coming originally from the Czech word "robota", meaning "labor". More recently, computer assistance and robotics based in the telepresence and virtual reality concept have been applied ...

A 9 mRNAs-based diagnostic signature for rheumatoid arthritis by integrating bioinformatic analysis and machine-learning.

Journal of orthopaedic surgery and research
BACKGROUND: Rheumatoid arthritis (RA) is an autoimmune rheumatic disease that carries a substantial burden for both patients and society. Early diagnosis of RA is essential to prevent disease progression and select an optimal therapeutic strategy. Ho...

Forecasting annual natural gas consumption via the application of a novel hybrid model.

Environmental science and pollution research international
Accurate prediction of natural gas consumption (NGC) can offer effective information for energy planning and policy-making. In this study, a novel hybrid forecasting model based on support vector machine (SVM) and improved artificial fish swarm algor...

Transfer Learning for COVID-19 cases and deaths forecast using LSTM network.

ISA transactions
In this paper, Transfer Learning is used in LSTM networks to forecast new COVID cases and deaths. Models trained in data from early COVID infected countries like Italy and the United States are used to forecast the spread in other countries. Single a...

Information Aware max-norm Dirichlet networks for predictive uncertainty estimation.

Neural networks : the official journal of the International Neural Network Society
Precise estimation of uncertainty in predictions for AI systems is a critical factor in ensuring trust and safety. Deep neural networks trained with a conventional method are prone to over-confident predictions. In contrast to Bayesian neural network...