Eli Snir
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View article: Forecasting world health expenditures: A hybrid artificial intelligence framework
Forecasting world health expenditures: A hybrid artificial intelligence framework Open
Global healthcare expenditures continue to rise, posing substantial economic challenges, particularly for low- and middle-income countries (LMICs), where resource constraints intensify the impact. Accurate forecasting, efficient resource a…
View article: Classifying seismic event parameters using artificial intelligence
Classifying seismic event parameters using artificial intelligence Open
Seismic events present a significant global threat, underscoring the need for effective models to provide insights into these natural disasters. This paper addresses the critical need for advanced seismic event analysis by combining tradit…
View article: LEVERAGING COMPUTER VISION AND NATURAL LANGUAGE PROCESSING FOR OBJECT DETECTION AND LOCALIZATION
LEVERAGING COMPUTER VISION AND NATURAL LANGUAGE PROCESSING FOR OBJECT DETECTION AND LOCALIZATION Open
This paper presents a novel approach leveraging the integration of Computer Vision, Natural Language Processing (NLP), and Speech Recognition technologies to create an AI-powered system capable of detecting and locating objects through voi…
View article: PTSD Case Detection with Boosting
PTSD Case Detection with Boosting Open
In this project, the electroencephalogram (EEG) channel(s) is used to better characterize post-traumatic stress disorder (PTSD). For this aim, we applied boosting methods along with a combination of k-means and Support Vector Machine (SVM)…
View article: Dental cavity analysis, prediction, localization, and quantification using computer vision
Dental cavity analysis, prediction, localization, and quantification using computer vision Open
Dental health assessment is a critical component of overall well-being, and advancements in computer vision and deep learning have opened new avenues for automating and enhancing this process. In this study, we present a comprehensive appr…
View article: Naïve Bayes and Random Forest for Crop Yield Prediction
Naïve Bayes and Random Forest for Crop Yield Prediction Open
This study analyzes crop yield prediction in India from 1997 to 2020, focusing on various crops and key environmental factors. It aims to predict agricultural yields by utilizing advanced machine learning techniques like Linear Regression,…
View article: Classifying and Forecasting Seismic Event Characteristics Using Artificial Intelligence
Classifying and Forecasting Seismic Event Characteristics Using Artificial Intelligence Open
Seismic events present a significant global threat, underscoring the need for effective models to provide insights into these natural disasters. This paper addresses the critical need for advanced seismic event analysis by combining tradit…
View article: Naïve Bayes and Random Forest for Crop Yield Prediction
Naïve Bayes and Random Forest for Crop Yield Prediction Open
This study analyzes crop yield prediction in India from 1997 to 2020, focusing on various crops and key environmental factors. It aims to predict agricultural yields by utilizing advanced machine learning techniques like Linear Regression,…
View article: PTSD Case Detection with Boosting
PTSD Case Detection with Boosting Open
In this project the EEG – electroencephalogram - channel(s) will be characterized to diagnose PTSD – Post-traumatic stress disorder – cases. For this aim, we applied boosting methods including a combination of K-mean and Support Vector Mac…
View article: COVID-19 Does Not Correlate with the Temperature
COVID-19 Does Not Correlate with the Temperature Open
The coronavirus disease 2019 (Covid-19) is now a global health crisis. According to the World Health Organization Situation Report, the number of Covid-19 confirmed cases reached 10,185,374 globally as of June 30, 2020.With global temperat…
View article: Machine Learning dimensionality reduction to detect EEG channeldifferences between PTSD cases and healthy controls
Machine Learning dimensionality reduction to detect EEG channeldifferences between PTSD cases and healthy controls Open
The goal of this study is to characterize EEG channel(s) that can help distinguish between PTSD and Healthy cases. For this purpose, we introduce a dimensionality reduction method that combines clustering and Support Vector Machine (SVM) w…
View article: Machine Learning Classifiers Help to Manage COVID-19 Distribution in China
Machine Learning Classifiers Help to Manage COVID-19 Distribution in China Open
The coronavirus disease 2019 (COVID-19) first appeared in Wuhan, China in December 2019. It spread very quickly from Hubei to the rest of China within only 30 days [1]. As of February 14, 2020, 78.91% of the total confirmed cases in China …
View article: Machine Learning Classifiers Help to Manage COVID-19 Distribution in ChinaThe coronavirus disease 2019 (COVID-19) first appeared in Wuhan, China in December 2019. It spread very quickly from Hubei to the rest of China within only 30 days [1]. As of February 14, 2020, 78.91% of the total confirmed cases in China were in Hubei province which is in midland China and 60.33% of the total confirmed cases in Hubei were in Wuhan [2]. In this project we use K-Means clustering and regression analysis to classify the cities in China based on location and infection rate. The goal is analyzing the demographic and geographic characteristics of the clusters containing less than 5 members with high infection rate. We found that all the cities in the smal (Preprint)
Machine Learning Classifiers Help to Manage COVID-19 Distribution in ChinaThe coronavirus disease 2019 (COVID-19) first appeared in Wuhan, China in December 2019. It spread very quickly from Hubei to the rest of China within only 30 days [1]. As of February 14, 2020, 78.91% of the total confirmed cases in China were in Hubei province which is in midland China and 60.33% of the total confirmed cases in Hubei were in Wuhan [2]. In this project we use K-Means clustering and regression analysis to classify the cities in China based on location and infection rate. The goal is analyzing the demographic and geographic characteristics of the clusters containing less than 5 members with high infection rate. We found that all the cities in the smal (Preprint) Open
BACKGROUND COVID 19 is an infectious disease which is caused by the coronavirus. It is currently spreading worldwide at a faster rate since it was first reported in Wuhan city in China in 2019 [3]. WHO declared COVID 19 as a world pandemi…