Software for Rapid Detection of Dyslexia Developed in Russia
HSE scientists have developed a software tool for assessing the presence and degree of dyslexia in school students based on their gender, age, school grade, and eye-tracking data. The application is expected to be introduced into clinical practice in 2024. The underlying studies were conducted by specialists in machine learning and neurolinguistics at the HSE AI Research Centre.
The software, which employs a machine learning model for diagnosing reading disorders in children based on eye-tracking data, is intended for use by psychologists, speech therapists, and medical practitioners.
The application—Dyslector—will be accessible across multiple platforms, including desktop computers running Windows and macOS, as well as mobile devices operating on Android and iOS. While the participant reads sentences from a laptop screen or mobile device, their eye movements are captured using an eye-tracker. The software user inputs the participant's gender, school grade, and age, along with the time and coordinates of gaze fixation, and the software generates information regarding the risk of dyslexia or confirming its presence.
The software does not require the involvement of a data scientist and makes it possible, within a very short time, to detect reading disorders in children and confirm the presence of dyslexia. Upon entering the necessary data, the user clicks the 'Assess Degree of Dyslexia' button, and the application displays the model's prediction: normal, risk of dyslexia, or dyslexia.
Director of the Centre for Language and Brain, Head of the project 'Diagnostic and assistive speech technologies based on artificial intelligence' at the HSE AI Research Centre
'The machine learning methods employed in this project rely on extensive and unique bodies of data. The software makes it possible to detect dyslexia risk in children based on eye movements and to assess the oculomotor parameters that could contribute to reading difficulties. A unique aspect of this tool is its ability to detect reading disorders or dyslexia within a very brief period, unlike traditional neuropsychological or speech therapy assessments, which typically require significantly more time and the involvement of a specialist.'
The AI Research Centre was created at HSE University as part of the 'Artificial Intelligence’ federal project within the 'Digital Economy' national programme.
See also:
‘The Goal of the Spring into ML School Is to Unite Young Scientists Engaged in Mathematics of AI’
The AI and Digital Science Institute at the HSE Faculty of Computer Science and Innopolis University organised a week-long programme for students, doctoral students, and young scientists on the application of mathematics in machine learning and artificial intelligence. Fifty participants of Spring into ML attended 24 lectures on machine learning, took part in specific pitch sessions, and completed two mini-courses on diffusion models—a developing area of AI for data generation.
‘Every Article on NeurIPS Is Considered a Significant Result’
Staff members of the HSE Faculty of Computer Science will present 12 of their works at the 37th Conference and Workshop on Neural Information Processing Systems (NeurIPS), one of the most significant events in the field of artificial intelligence and machine learning. This year it will be held on December 10–16 in New Orleans (USA).
HSE University Holds HSE Sber ML Hack
On November 17-19, The HSE Faculty of Computer Science, SBER and cloud technology provider Cloud.ru organised HSE Sber ML Hack, a hackathon based around machine learning. More than 350 undergraduate and graduate students from 54 leading Russian universities took part in the competition.
HSE University Hosts Fall into ML 2023 Conference on Machine Learning
Over three days, more than 300 conference participants attended workshops, seminars, sections and a poster session. During panel discussions, experts deliberated on the regulation of artificial intelligence (AI) technologies and considered collaborative initiatives between academic institutions and industry to advance AI development through megaprojects.
HSE University to Host ‘Fall into ML 2023’ Machine Learning Conference
Machine Learning (ML) is a field of AI that examines methods and algorithms that enable computers to learn based on experience and data and without explicit programming. With its help, AI can analyse data, recall information, build forecasts, and give recommendations. Machine learning algorithms have applications in medicine, stock trading, robotics, drone control and other fields.
New Labs to Open at Faculty of Computer Science
Based on the results of a project competition, two new laboratories are opening at HSE University’s Faculty of Computer Science. The Laboratory for Matrix and Tensor Methods in Machine Learning will be headed by Maxim Rakhuba, Associate Professor at the Big Data and Information Retrieval School. The Laboratory for Cloud and Mobile Technologies will be headed by Dmitry Alexandrov, Professor at the School of Software Engineering.
Joint Project of Scientists from HSE University and Surgut State University to Help Prevent Recurrent Heart Attacks and Strokes
One of the winning projects of a competition held by HSE University’s Mirror Laboratories last June focuses on the use of machine learning technologies to predict the outcomes of acute coronary syndrome. It is implemented by HSE University’s International Laboratory of Bioinformatics together with the Research and Educational Centre of the Medical Institute at Surgut State University. Maria Poptsova, Head of the International Laboratory of Bioinformatics and Associate Professor at HSE University’s Faculty of Computer Science, talks about how this joint project originated, how it will help patients, and how work to implement it will be organised.
‘Interest in the Application of Machine Learning in Bioinformatics Is Growing by the Year’
On August 28–30, HSE University’s Faculty of Computer Science held the 4th Summer School on Machine Learning in Bioinformatics. This year, 670 people registered for the event, and over 300 visited in person. The programme included lectures and seminars on various spheres of bioinformatics: applied bioinformatics and the bioinformatics of DNA, RNA, and proteins; elementary genomics; modern methods of data analysis and molecular biology. The lectures were complemented by practical tasks aimed at different levels of knowledge.
Fall into ML 2023: HSE University’s Faculty of Computer Science Organises Conference on Machine Learning
On October 26–28, HSE University’s Institute of Artificial Intelligence and Digital Sciences at the Faculty of Computer Science will hold a conference titled Fall into ML 2023 withsupport from the HSE University AI Research Centre . The event is dedicated to promising directions of fundamental AI development.
HSE Researchers Examine Wellbeing of Russian Social Media Users and Rank Public Holidays by Popularity
Researchers of the HSE Graduate School of Business trained a machine-learning (ML) model to infer users' subjective wellbeing from social media posts. Having processed 10 million tweets, the researchers compiled a rating of holidays celebrated in Russia based on their popularity. The New Year tops the list, but Russian-speaking users of Twitter are also happy to celebrate Defender of the Fatherland Day, International Women's Day, and Halloween. The study findings have been published in PeerJ Computer Science.