Machine learning approach for autonomous detection and classification of COVID-19 virus
As people all over the world are vulnerable to be affected by the COVID-19 virus, the
automatic detection of such a virus is an important concern. The paper aims to detect and …
automatic detection of such a virus is an important concern. The paper aims to detect and …
Transforming Payment Processes: A Discussion of AI-Enabled Routing Optimization
The utilization of Artificial Intelligence (AI)-enabled software and hardware is expected to
enhance the effectiveness of monetary exchanges, which is the main objective of this …
enhance the effectiveness of monetary exchanges, which is the main objective of this …
[HTML][HTML] COVID-19 detection and classification for machine learning methods using human genomic data
MT Ahemad, MA Hameed, R Vankdothu - Measurement: Sensors, 2022 - Elsevier
Coronavirus is a disease connected to coronavirus. World Health Organization has declared
COVID-19 a pandemic. It has an impact on 212 nations and territories worldwide. Examining …
COVID-19 a pandemic. It has an impact on 212 nations and territories worldwide. Examining …
[PDF][PDF] A review and meta-analysis of machine intelligence approaches for mental health issues and depression detection
Cases of mental health issues are increasing continuously and have sped up due to COVID-
19. There are high chances of developing mental health issues such as depression, anxiety …
19. There are high chances of developing mental health issues such as depression, anxiety …
Deep learning and evolutionary intelligence with fusion-based feature extraction for detection of COVID-19 from chest X-ray images
In recent times, COVID-19 infection gets increased exponentially with the existence of a
restricted number of rapid testing kits. Several studies have reported the COVID-19 …
restricted number of rapid testing kits. Several studies have reported the COVID-19 …
[PDF][PDF] Medical data clustering and classification using TLBO and machine learning algorithms
This study aims to empirically analyze teaching-learning-based optimization (TLBO) and
machine learning algorithms using k-means and fuzzy c-means (FCM) algorithms for their …
machine learning algorithms using k-means and fuzzy c-means (FCM) algorithms for their …
Self-health analysis with two step histogram based procedure using machine learning
Machine learning is the critical tool in the future for prediction in the real-time to analyze the
self-health of the person. The self-health is the motivation for the patient who is suffering …
self-health of the person. The self-health is the motivation for the patient who is suffering …
Analyzing the growing factor of Financial Markets Using Sentimental Analysis Algorithms
P Kantha, N Thiyagarajan, V Sharma… - 2023 Annual …, 2023 - ieeexplore.ieee.org
Sentiment analysis algorithms have grown to be increasingly famous within the economic
markets. Those algorithms process consumer-generated facts to expect market moves …
markets. Those algorithms process consumer-generated facts to expect market moves …
[PDF][PDF] Evaluation of using parametric and non-parametric machine learning algorithms for covid-19 forecasting
Machine learning prediction algorithms are considered powerful tools that could provide
accurate insights about the spread and mortality of the novel Covid-19 disease. In this …
accurate insights about the spread and mortality of the novel Covid-19 disease. In this …
[PDF][PDF] Computational decision support system in healthcare: a review and analysis
R Chahar - International Journal of Advanced Technology and …, 2021 - researchgate.net
A decision support system (DSS) may help to synchronize comprehensive computational
aspects of computational problems like knowledge discovery, processing, and pattern …
aspects of computational problems like knowledge discovery, processing, and pattern …