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Forecasting

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A new rainfall prediction model based on ICEEMDAN-WSD-BiLSTM and ESN.

Environmental science and pollution research international
Precipitation, as an important indicator describing the evolution of the regional climate system, plays an important role in understanding the spatial and temporal distribution characteristics of regional precipitation. Scientific and accurate predic...

Putting the Personalized Metabolic Avatar into Production: A Comparison between Deep-Learning and Statistical Models for Weight Prediction.

Nutrients
Nutrition is a cross-cutting sector in medicine, with a huge impact on health, from cardiovascular disease to cancer. Employment of digital medicine in nutrition relies on digital twins: digital replicas of human physiology representing an emergent s...

Enhanced Neural Network-Based Univariate Time-Series Forecasting Model for Big Data.

Big data
Big data is a combination of large structured, semistructured, and unstructured data collected from various sources that must be processed before using them in many analytical applications. Anomalies or inconsistencies in big data refer to the occurr...

Incorporating variant frequencies data into short-term forecasting for COVID-19 cases and deaths in the USA: a deep learning approach.

EBioMedicine
BACKGROUND: Since the US reported its first COVID-19 case on January 21, 2020, the science community has been applying various techniques to forecast incident cases and deaths. To date, providing an accurate and robust forecast at a high spatial reso...

Medical multivariate time series imputation and forecasting based on a recurrent conditional Wasserstein GAN and attention.

Journal of biomedical informatics
OBJECTIVE: In the fields of medical care and research as well as hospital management, time series are an important part of the overall data basis. To ensure high quality standards and enable suitable decisions, tools for precise and generic imputatio...

Deep-Learning Model for Influenza Prediction From Multisource Heterogeneous Data in a Megacity: Model Development and Evaluation.

Journal of medical Internet research
BACKGROUND: In megacities, there is an urgent need to establish more sensitive forecasting and early warning methods for acute respiratory infectious diseases. Existing prediction and early warning models for influenza and other acute respiratory inf...

Data-driven prediction of greenhouse aquaponics air temperature based on adaptive time pattern network.

Environmental science and pollution research international
Greenhouse aquaponics system (GHAP) improves productivity by harmonizing internal environments. Keeping a suitable air temperature of GHAP is essential for the growth of plant and fish. However, the disturbance of various environmental factors and th...

Insights and trends review: artificial intelligence in hand surgery.

The Journal of hand surgery, European volume
Artificial intelligence (AI) in hand surgery is an emerging and evolving field that will likely play a large role in the future care of our patients. However, there remain several challenges to makes this technology meaningful, acceptable and usable ...

Building an automated, machine learning-enabled platform for predicting post-operative complications.

Physiological measurement
. In 2019, the University of Florida College of Medicine launched thealgorithm to predict eight major post-operative complications using automatically extracted data from the electronic health record.. This project was developed in parallel with our ...