AIMC Topic: Forecasting

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Artificial intelligence platform to predict children's hospital care for respiratory disease using clinical, pollution, and climatic factors.

Journal of global health
BACKGROUND: Hospitals and health care systems may benefit from artificial intelligence (AI) and big data to analyse clinical information combined with external sources. Machine learning, a subset of AI, uses algorithms trained on data to generate pre...

Baltic dry index forecast using financial market data: Machine learning methods and SHAP explanations.

PloS one
The Baltic Dry Index (BDI) is a critical benchmark for assessing freight rates and chartering activity in the global shipping market. This study forecasts the BDI using diverse financial data, including commodities, currencies, stock markets, and vol...

Simulation-based training in minimally invasive surgical therapies (MIST): current evidence and future directions for artificial intelligence integration-a systematic review by EAU endourology.

World journal of urology
INTRODUCTION: Benign prostatic hyperplasia (BPH) affects a growing proportion of the aging male population. Minimally invasive surgical therapies (MISTs) such as Rezum and UroLift offer effective alternatives to traditional approaches like transureth...

Forecasting birth trends in Ethiopia using time-series and machine-learning models: a secondary data analysis of EDHS surveys (2000-2019).

BMJ open
OBJECTIVE: Ethiopia, the second most populous country in Africa, faces significant demographic transitions, with fertility rates playing a central role in shaping economic and healthcare policies. Family planning programmes face challenges due to fun...

Genome sequencing is critical for forecasting outcomes following congenital cardiac surgery.

Nature communications
While exome and whole genome sequencing have transformed medicine by elucidating the genetic underpinnings of both rare and common complex disorders, its utility to predict clinical outcomes remains understudied. Here, we use artificial intelligence ...

Application effect of short-term traffic flow prediction method based on CNNBLSTM algorithm.

PloS one
Reduced forecast efficiency and accuracy are the result of traditional traffic flow prediction algorithms' inability to adequately capture the spatiotemporal characteristics and dynamic changes of traffic flow. To address this problem, this study pro...

Empirical study of daily link traffic volume forecasting based on a deep neural network.

PloS one
Forecasting the daily link traffic volume is critical in transportation demand analysis in feasibility studies for planning transportation facilities. The high purchase and maintenance cost of commercial transport planning software poses a challenge ...

A big data driven multilevel deep learning framework for predicting terrorist attacks.

Scientific reports
In recent years, terrorism has increasingly threatened human security, causing violence, fear, and damage to both the general public and specific targets. These attacks create unrest among individuals and within society. Leveraging the recent advance...

Artificial neural network-driven approaches to improved forecasting of disability care expenditures in an aging Kingdom of Saudi Arabia population.

Scientific reports
The total number of older persons globally (those aged 60 years and above) was 202 million in 1950; this total multiplied to attain 901 million and is predicted to triple again in 2100. The growth percentage of the elderly population is quickly impro...

The Future of Questions.

Journal of continuing education in nursing
As we move into the artificial intelligence decade, with more emphasis on creativity and innovation, it will be important to ask questions in a different way. It will be critical for leaders and faculty to think about questions they haven't asked in ...