AIMC Topic: Forecasting

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Current Status and Future Perspectives of Robot-Assisted Dental Implant Surgery.

International dental journal
Dental implant surgery is now a well versed approach for tooth replacement, addressing various limitations of fixed bridges and removable dentures, thereby reinstating both the form and function of missing teeth. However, it is technically sensitive ...

Artificial Intelligence Use in Medical Education: Best Practices and Future Directions.

Current urology reports
PURPOSEOF REVIEW: This review examines the various ways artificial intelligence (AI) has been utilized in medical education (MedEd)and presents ideas that will ethically and effectively leverage AI in enhancing the learning experience of medical trai...

Multivariate forecasting of dengue infection in Bangladesh: evaluating the influence of data downscaling on machine learning predictive accuracy.

BMC infectious diseases
The increasing incidence of dengue virus (DENV) infections poses significant public health challenges in Bangladesh, demanding advanced forecasting methodologies to guide timely interventions. This study introduces a rigorous multivariate time series...

Intelligent traffic congestion forecasting using BiLSTM and adaptive secretary bird optimizer for sustainable urban transportation.

Scientific reports
Traffic congestion forecasting is one of the major elements of the Intelligent Transportation Systems (ITS). Traffic congestion in urban road networks significantly influences sustainability by increasing air pollution levels. Efficient congestion ma...

Forecasting Surgical Bed Utilization: Architectural Design of a Machine Learning Pipeline Incorporating Predicted Length of Stay and Surgical Volume.

Journal of medical systems
The objective of this study was to develop a machine learning model utilizing data from the electronic health record (EHR) to model length of stay and daily surgical volume, in order to subsequently predict daily surgical inpatient bed utilization. M...

Predicting hospital outpatient volume using XGBoost: a machine learning approach.

Scientific reports
Hospital outpatient volume is influenced by a variety of factors, including environmental conditions and healthcare resource availability. Accurate prediction of outpatient demand can significantly enhance operational efficiency and optimize the allo...

GCN-Transformer: Graph Convolutional Network and Transformer for Multi-Person Pose Forecasting Using Sensor-Based Motion Data.

Sensors (Basel, Switzerland)
Multi-person pose forecasting involves predicting the future body poses of multiple individuals over time, involving complex movement dynamics and interaction dependencies. Its relevance spans various fields, including computer vision, robotics, huma...

Forecasting Banned Substances: Leveraging GNN and Explainable AI for Sports Anti-Doping.

Studies in health technology and informatics
Ensuring fairness in competitive sports requires robust mechanisms for detecting prohibited substances. Despite established regulations, challenges persist in accurately identifying new and emerging doping agents. This study introduces the use of Gra...

AI-driven approaches for air pollution modelling: A comprehensive systematic review.

Environmental pollution (Barking, Essex : 1987)
In recent years, air quality levels have become a global issue with the rise of harmful pollutants and their effects on climate change. Urban areas are especially affected by air pollution, resulting in a deterioration of the environment and a surge ...