AIMC Topic: Forecasting

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A Review on an Artificial Intelligence Based Ophthalmic Application.

Current pharmaceutical design
Artificial intelligence is the leading branch of technology and innovation. The utility of artificial intelligence in the field of medicine is also remarkable. From drug discovery and development to introducing products to the market, artificial inte...

[Development of Clinical Pharmaceutical Services via Artificial Intelligence Adaptation].

Yakugaku zasshi : Journal of the Pharmaceutical Society of Japan
Recently, social implementations of artificial intelligence (AI) have been rapidly advancing. Many papers have investigated the use of AI in the field of healthcare. However, there have been few studies on the adaptation of AI to clinical pharmaceuti...

Foundations of Time Series Analysis.

Acta neurochirurgica. Supplement
For almost a century, classical statistical methods including exponential smoothing and autoregression integrated moving averages (ARIMA) have been predominant in the analysis of time series (TS) and in the pursuit of forecasting future events from h...

Artificial Intelligence for Brain Molecular Imaging.

PET clinics
AI has been applied to brain molecular imaging for over 30 years. The past two decades, have seen explosive progress. AI applications span from operations processes such as attenuation correction and image generation, to disease diagnosis and predict...

AI-based forecasting of ethanol fermentation using yeast morphological data.

Bioscience, biotechnology, and biochemistry
Several industries require getting information of products as soon as possible during fermentation. However, the trade-off between sensing speed and data quantity presents challenges for forecasting fermentation product yields. In this study, we trie...

Robust forecasting using predictive generalized synchronization in reservoir computing.

Chaos (Woodbury, N.Y.)
Reservoir computers (RCs) are a class of recurrent neural networks (RNNs) that can be used for forecasting the future of observed time series data. As with all RNNs, selecting the hyperparameters in the network to yield excellent forecasting presents...