Improving drug review categorization using sentiment analysis and machine learning
Content created by users from social media platforms has become increasingly important as
the internet has grown, and it now contains a plethora of knowledge regarding medications …
the internet has grown, and it now contains a plethora of knowledge regarding medications …
Pandemic outbreak time: Evaluation of public tweet opinion by machine learning
In this work, a Twitter data-set was utilized to do sentiment analysis of people's thoughts on
the corona-virus (COVID-19) period, which is a major concern throughout the world these …
the corona-virus (COVID-19) period, which is a major concern throughout the world these …
Deep learning for multi-labeled cyberbully detection: Enhancing online safety
Social media platforms offer undeniable benefits, but the preservation of anonymity has led
to the emergence of cyberbullying, a concerning social problem. This form of online …
to the emergence of cyberbullying, a concerning social problem. This form of online …
Bangladeshi traffic sign recognition and classification using cnn with different kinds of transfer learning through a new (btsrb) dataset
An accident is the cry of a lifetime. The role of traffic signs is most important in preventing or
mitigating accidents. In many cases, while driving, traffic signs are not visible in the …
mitigating accidents. In many cases, while driving, traffic signs are not visible in the …
Alzheimer Disease Classification Using Deep Neural Network
Alzheimer's disease is a complex neurodegenerative disorder with profound implications for
individuals and healthcare systems. Early and accurate diagnosis is critical for effective …
individuals and healthcare systems. Early and accurate diagnosis is critical for effective …
An adaptive traffic signal management system incorporating reinforcement learning
Although there has been a lot of study done on traffic monitoring, control, modeling, and the
use of artificial intelligence to handle these problems, there are still a lot of critical problems …
use of artificial intelligence to handle these problems, there are still a lot of critical problems …
Comparative analysis of epileptic seizure prediction: Exploring diverse pre-processing techniques and machine learning models
MSH Talukder, RB Sulaiman… - 2023 10th IEEE Uttar …, 2023 - ieeexplore.ieee.org
Precise prediction and detection of epilepsy, a common neurological condition marked by
sporadic and repeated seizures, is necessary for efficient management and patient care. To …
sporadic and repeated seizures, is necessary for efficient management and patient care. To …
Deep learning-based left ventricular ejection fraction estimation from echocardiographic videos
Heart failure (HF) is a prevalent and life-threatening medical condition afflicting millions of
people worldwide. A critical parameter in assessing cardiac function and detecting HF is the …
people worldwide. A critical parameter in assessing cardiac function and detecting HF is the …
Migrating to Big Data: Contextual Challenges for Data-driven Success
MR Naqvi, SK Shahzad, G Chhabra… - 2023 10th IEEE Uttar …, 2023 - ieeexplore.ieee.org
Many database operational and analytical systems are adopting Big Data analytics tools
and techniques to meet the upcoming business challenges. Migration to Hadoop Distributed …
and techniques to meet the upcoming business challenges. Migration to Hadoop Distributed …
Deep Learning Based Tuberculosis and Pneumonia Disease Detection Using CNN
Tuberculosis and pneumonia are debilitating respiratory diseases that pose significant
health challenges around the world. For these disorders to be treated and controlled …
health challenges around the world. For these disorders to be treated and controlled …