Hello Sythalakshmi Cs

This topic is relevant. Given the application of machine learning in the educational sphere is vast. Most researchers use it to predict student drop-out hence if you want to see how it can detect learning disabilities in kids with a view to offer recommendations that will help the teachers as well as academic administrators then it is a welcome adventure.

Here are some articles that might help your quest

Article A preliminary evaluation of still face images by deep learni...

Article Developmental dyslexia detection using machine learning tech...

if you find this useful, drop a recommendation.. Regards

Hello Sythalakshmi Cs

This topic is relevant. Given the application of machine learning in the educational sphere is vast. Most researchers use it to predict student drop-out hence if you want to see how it can detect learning disabilities in kids with a view to offer recommendations that will help the teachers as well as academic administrators then it is a welcome adventure.

Here are some articles that might help your quest

Article A preliminary evaluation of still face images by deep learni...

Article Developmental dyslexia detection using machine learning tech...

if you find this useful, drop a recommendation.. Regards

Thank you sir..

Sure sir..

Sythalakshmi Cs Please consult the following works:

Chapter Using Machine Learning to Help Students with Learning Disabi...

Article Remapping the cognitive and neural profiles of children who ...

https://ieeexplore.ieee.org/document/8076796

https://theeconomyofmeaning.com/2018/10/01/using-ai-to-discover-learning-disabilities-in-children/

https://www.technologyreview.com/2017/03/23/68727/machine-learning-opens-up-new-ways-to-help-disabled-people/

https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.299.6109&rep=rep1&type=pdf

Article A survey paper on learning disability prediction using machi...

Article Machine Learning and Dyslexia: Diagnostic and Classification...

Article Developmental dyslexia detection using machine learning tech...

http://vision.soic.indiana.edu/detecting-dyslexia-using-neural-networks/

https://aiforsocialgood.github.io/icml2019/accepted/track1/pdfs/43_aisg_icml2019.pdf

https://medium.com/@kenedywaweru07/9-ways-artificial-intelligence-is-making-learning-easier-for-kids-with-learning-disabilities-d77f31b57b6a

http://www.mecs-press.org/ijisa/ijisa-v5-n12/IJISA-V5-N12-3.pdf

Article Early Prediction of Reading Disability using Machine Learning

Preprint Dyslexia and Dysgraphia prediction: A new machine learning approach

would like to express my deep appreciation to those teachers who took part in ... work that is interesting and will hopefully be of some support to teachers of ... Teaching Children with Learning Difficulties: The Experiences of Primary ... Despite these limitations, a key finding of the study was that the total number of students

This paper highlights the two machine learning approaches, viz. Rough Sets and Decision Trees (DT), for the prediction of Learning Disabilities (LD) in school-age children, with an emphasis on applications of data mining. Learning disability prediction is a very complicated task. By using these two approaches, we can easily and accurately predict LD in any child and also we can determine the best classification method. In this study, in rough sets the attribute reduction and classification are performed using Johnson’s reduction algorithm and Naive Bayes algorithm respectively for rule mining and in construction of decision trees, J48 algorithm is used. From this study, it is concluded that, the performance of decision trees are considerably poorer in several important aspects compared to rough sets. It is found that, for selection of attributes, rough sets is very useful especially in the case of inconsistent data and it also gives the information about the attribute correlation which is very important in the case of learning disability.

Article Machine Learning Approach for Prediction of Learning Disabil...

2021 chapter Chapter Machine learning

In the last few years, especially thanks to the recent advancements in the field of Deep Learning, Machine Learning has drawn a lot of attention. One of the main driving factors of the machine learning hype is related to the fact that it offers a unified framework for introducing intelligent decision-making into many domains. In the following chapters, we will introduce examples of possible applications of machine learning to networking scenarios. Here we will lay the foundation to start diving into the machine learning world. We start by discussing various categories of machine learning algorithms. Then we introduce the needed mathematical notation. Finally, we introduce and discuss the most common algorithms for supervised learning and reinforcement learning.

2019,

Conference Paper Mathematical modeling combined with machine learning for soc...

Read this chapter

Using Machine Learning to Help Students with Learning Disabilities Learn