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Forecasting

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Personalized glucose forecasting for people with type 1 diabetes using large language models.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Type 1 Diabetes (T1D) is an autoimmune disease that requires exogenous insulin via Multiple Daily Injections (MDIs) or subcutaneous pumps to maintain targeted glucose levels. Despite the advances in Continuous Glucose Monito...

TCN-QV: an attention-based deep learning method for long sequence time-series forecasting of gold prices.

PloS one
Accurate prediction of gold prices is crucial for investment decision-making and national risk management. The time series data of gold prices exhibits random fluctuations, non-linear characteristics, and high volatility, making prediction extremely ...

Confidence interval forecasting model of small watershed flood based on compound recurrent neural networks and Bayesian.

PloS one
Flood forecasting exhibits rapid fluctuations, water level forecasting shows great uncertainty and inaccuracy in small watersheds, and the reliability and accuracy performance of traditional probability forecasting is often unbalanced. This study com...

The future outlook for data in orthopedic surgery: A new era of real-time innovation.

Journal of orthopaedic surgery (Hong Kong)
The orthopedic field is on the brink of a significant transformation-a shift from retrospective analysis to real-time decision-making fueled by data. The dependence on historical trends or long-term studies is yielding to an era where data flows dyna...

Current applications and future perspectives of artificial intelligence in functional urology and neurourology: how far can we get?

Minerva urology and nephrology
In the last few years, the scientific community has seen an increasing interest towards the potential applications of artificial intelligence in medicine and healthcare. In this context, urology represents an area of rapid development, particularly i...

[Artificial intelligence in Public Health: opportunities, ethical challenges and future perspectives].

Revista espanola de salud publica
Artificial Intelligence (AI) is transforming Public Health by providing innovative tools to address complex global challenges. Its ability to analyze large volumes of data in real time enhances epidemiological surveillance, optimizes healthcare resou...

Prediction of outpatient visits for allergic rhinitis using an artificial intelligence LSTM model - a study in Eastern China.

BMC public health
BACKGROUND: Allergic rhinitis is a common disease that can affect the health of patients and bring huge social and economic burdens. In this study, we developed a model to predict the incidence rate of allergic rhinitis so as to provide accurate info...

Predictive modeling of climate change impacts using Artificial Intelligence: a review for equitable governance and sustainable outcome.

Environmental science and pollution research international
The accelerating pace of climate change poses unprecedented challenges to global ecosystems and human societies. In response, this study reviews the power of Artificial Intelligence (AI) to develop advanced predictive models for assessing the multifa...

Forecasting motion trajectories of elbow and knee joints during infant crawling based on long-short-term memory (LSTM) networks.

Biomedical engineering online
BACKGROUND: Hands-and-knees crawling is a promising rehabilitation intervention for infants with motor impairments, while research on assistive crawling devices for rehabilitation training was still in its early stages. In particular, precisely gener...

The generative revolution: AI foundation models in geospatial health-applications, challenges and future research.

International journal of health geographics
In an era of rapid technological advancements, generative artificial intelligence and foundation models are reshaping industries and offering new advanced solutions in a wide range of scientific areas, particularly in public and environmental health....