An innovative neural network approach for stock market prediction
This paper aims to develop an innovative neural network approach to achieve better stock
market predictions. Data were obtained from the live stock market for real-time and off-line …
market predictions. Data were obtained from the live stock market for real-time and off-line …
Detection of brain tumor based on features fusion and machine learning
Automated detection of brain tumor is a more challenging work due to the variability and
complexity of shape, size, texture and location of lesions. The non-invasive MRI methods …
complexity of shape, size, texture and location of lesions. The non-invasive MRI methods …
A state-of-the-art technique to perform cloud-based semantic segmentation using deep learning 3D U-Net architecture
Glioma is the most aggressive and dangerous primary brain tumor with a survival time of
less than 14 months. Segmentation of tumors is a necessary task in the image processing of …
less than 14 months. Segmentation of tumors is a necessary task in the image processing of …
Air quality forecast using convolutional neural network for sustainable development in urban environments
The expansion of IT based technology has widely gathered and enhanced all the eras of
applicable domain to maintain the sustainable transformation. In fact, the new evolving …
applicable domain to maintain the sustainable transformation. In fact, the new evolving …
An optimized integrated framework of big data analytics managing security and privacy in healthcare data
Big data analytics has anonymously changed the overall global scenario to discover
knowledge trends for future decision making. In general, potential area of big data …
knowledge trends for future decision making. In general, potential area of big data …
Pre-emption of affliction severity using HRV measurements from a smart wearable; case-study on SARS-Cov-2 symptoms
Smart wristbands and watches have become an important accessory to fitness, but their
application to healthcare is still in a fledgling state. Their long-term wear facilitates extensive …
application to healthcare is still in a fledgling state. Their long-term wear facilitates extensive …
Dynamic Distributed and Parallel Machine Learning algorithms for big data mining processing
L Djafri - Data Technologies and Applications, 2022 - emerald.com
Purpose This work can be used as a building block in other settings such as GPU, Map-
Reduce, Spark or any other. Also, DDPML can be deployed on other distributed systems …
Reduce, Spark or any other. Also, DDPML can be deployed on other distributed systems …
Big Data analytics for prediction: parallel processing of the big learning base with the possibility of improving the final result of the prediction
L Djafri, D Amar Bensaber, R Adjoudj - Information Discovery and …, 2018 - emerald.com
Purpose This paper aims to solve the problems of big data analytics for prediction including
volume, veracity and velocity by improving the prediction result to an acceptable level and in …
volume, veracity and velocity by improving the prediction result to an acceptable level and in …
Big data analytics for prediction modelling in healthcare databases
Bigdata in healthcare has manifested as well as benefited healthcare practioners and
scientists around the globe to detect hidden patterns for future clinical decision making. The …
scientists around the globe to detect hidden patterns for future clinical decision making. The …
[HTML][HTML] Predictive modeling and web-based tool for cervical cancer risk assessment: A comparative study of machine learning models
In today's digital era, the rapid growth of databases presents significant challenges in data
management. In order to address this, we have developed and designed CHAMP (Cervical …
management. In order to address this, we have developed and designed CHAMP (Cervical …