Tagged / Natural Language Processing

CfACTs Workshop @ BFX-2024: Advances in Marking Medical Images with Natural Language Processing

BU research, Events, Research news, Uncategorized

On Wednessday 30’th of October, The Centre for Applied Creative Technologies (CfACTs)  arranged a workshop for AI Research Academics as part of the BFX-2024 Festival in Bournemouth.

BFX Festival is an annual conference that takes place in Bournemouth and Hilton Bournemouth through this week and since 28’th of October until 2nd of November.

Among the works presented during that session, the most-recent advances in Natural Language Processing application for marking medical images, presented by Dr. Nicolay Rusnachenko.

The purpose and keypont of the talk were as follows:

✅ Showcase the potentials of NLP appliaction in processing textual narratives ✍ via GenAI ChatGPT and other systems capable for the detailed explanation, necessary for High Quality data collection and further development the domain-oriented LLM. The following figure below showcases the importance on NLP application for processing medical narratives of liver-related MRI/CT scan series, such as one mentioned in "Series Descriptions" of the DICOM metadata.

✅ Propose the concept of the end-to-end solution for uniting automatic series understanding and assessing manually written narratives by novice practitioners ‍⚕️ using the GenAI as the Core Framework. The figure below illustrates the back-end and front-end components of the related system that serve with individual direction of scientific studies dedicated for enhancing domain oriented GenAI framework.

These advances were achieved while at Centre for Applied Creative Technologies CfACTs+ by working on “Marking Medical Image Reports Automatically with Natural Language Processing (NLP-MMI)” project.

Dr. Nicolay Rusnachenko
Research Fellow at Centre For Applied Creative Technologies PLUS (CFACT+)
Bournemouth University

Presenting Studies on LLMs Reasoning Capabilities in Sentiment Analysis of Mass-Media texts at NLPSummit-2024

BU research, conferences, Events, Knowledge Exchange, research methods, Uncategorized

 

As a part of reseach studies in Natural Langauge Processing (NLP) field, this year I am delighted to present the most recent advances of Generative AI in it at NLPSummit-2024. The 5’th summit represents a free online conference September 24-26, hosted by JohnSnowLabs. The conference is dedicated to showcase the best practices, real-world case studies and challanges in Generative AI for Natural Language Processing.

By joining to my talk you become aware of how Large Language Models (LLMs) could be applied for retrieving implicit information from non-structured texts. Sentiment Analysis represent one of such problems, and as a task aimed at extraction of the hidden opinion of the author towards objects mentioned in text. We start by discovering reasoning capabilities of the most popular Large Language Models (ChatGPT, Mistral, Gemma, Microsoft-Phi, and more) out-of-the-box to show their limitations in retrieving authors opinion from Mass-media texts. To address the existed limitations in models reasoning capabilities 🧠 , we cover Chain-of-Thought technique and explore the way of its proper adaptiation in Sentiment Analysis. It is worth to note that the techniques, to be covered, could be distributed and adapted in the other domains that go beyond Mass-media. Such domains include but are not limited to: medical (adverse drug reaction), literature (fictional chatbot development), conversational (emotion extaction / empathy mapping).

These advances were achieved while at Centre for Applied Creative Technologies CfACTs+ by working on “Marking Medical Image Reports Automatically with Natural Language Processing (NLP-MMI)” project.

The keylinks realted to the event and presentation in particular, are as follows:

📍 Event page: https://www.nlpsummit.org/nlp-summit-2024/
⏰ When: 24-26 September 2024 (Online)
⭐ Project: https://github.com/nicolay-r/Reasoning-for-Sentiment-Analysis-Framework

Dr. Nicolay Rusnachenko
Research Fellow at Centre For Applied Creative Technologies PLUS (CFACT+)
Bournemouth University