"nBackground: After the Islamic Revolution, the Iranian government aimed to improve the health status and reduce the inequality simultaneously.This study was conducted to explore the impact of the implemented programs."nMethods: we extensively reviewed published papers in Persian and English journals and explored grey literature, mainly t
Deep-Learning Model for Influenza Prediction From Multisource Heterogeneous Data in a Megacity: Model Development and Evaluation
BackgroundIn megacities, there is an urgent Tweed Breeks 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 infectious diseases have limitations and therefore there is room for improvement.ObjectiveThe
An Improved Method for Accurate Extraction of Coupling Coefficient Between a Lossy Radiator and a Lossless Resonator in Filtering Antennas
A unique method for accurate extraction of coupling coefficient between a lossy radiator and a lossless resonator is proposed in this paper to facilitate the synthesis design of filtering antennas.To remove the parasitic effect of the radiation loss in extraction of coupling coefficient, the network parameters of the coupled resonators in lossless
A Forecasting Approach to Online Change Detection in Land Cover Time Series
We present a method for online detection of land cover change based on remotely sensed time series.Change is detected by monitoring deviations between observations and forecasts made using the time series historical data and similar time series in the geographical region.This method and several others were applied to MODIS 8-day surface reflectance
Enhancing parasitic organism detection in microscopy images through deep learning and fine-tuned optimizer
Abstract Parasitic organisms pose a major global health threat, mainly in regions that lack advanced medical facilities.Early and accurate detection of parasitic organisms is vital to saving lives.Deep learning models have uplifted the medical sector by providing promising results in diagnosing, detecting, and classifying diseases.This paper explor