Domain-Specific NLP Rivals 70 Billion Parameter LLM Giants in Clinical AI

In our latest research, we set out to accurately classify Crohn’s disease (CD) in radiology reports using natural language processing (NLP).
Domain-Specific NLP Rivals 70 Billion Parameter LLM Giants in Clinical AI
Like

Share this post

Choose a social network to share with, or copy the URL to share elsewhere

This is a representation of how your post may appear on social media. The actual post will vary between social networks

📊 We evaluated a broad spectrum of NLP techniques—from rule-based models to rationale extraction, classic deep learning (CNN, Bi-LSTM) and LLMs.

🧠Meet IBDBERT 🤖 — our custom 110M-parameter transformer model finetuned on inflammatory bowel disease-specific textbooks and clinical guidelines (American Gastroenterological Association (AGA), American College of Gastroenterology, ECCO European Crohn' and Colitis Organisation). Despite being 600x smaller than today’s behemoths like Meta’s LLaMA 3.3-70B or DeepSeek-R1, IBDBERT achieved near or better than state-of-the-art performance.

💥The takeaway?
🧠Bigger isn’t always better. Domain-specific, efficient models can match or outperform billion-parameter LLMs—especially in specialized clinical settings.
📱Lightweight models like IBDBERT are well-suited for mobile or resource-limited settings, offering practical and scalable solutions without compromising accuracy, privacy, and energy efficiency.
🔍 Error analysis revealed that all models, including LLMs, overly relied on prior diagnosis sections rather than actual imaging findings—underscoring the need for explainable AI (XAI) in medicine.

📕Full paper
🔗https://www.nature.com/articles/s41746-025-01729-5

📖 Crohn’s Disease Background
🔗https://www.thelancet.com/article/S0140-6736(12)60026-9/fulltext
🔗https://doi.org/10.1007/978-3-319-33703-6

⚕️Crohn's Disease Management with Targeted Therapies
🔗https://www.nejm.org/doi/full/10.1056/NEJMra1907607

Follow the Topic

Inflammatory bowel disease
Life Sciences > Health Sciences > Clinical Medicine > Diseases > Immunological Disorders > Inflammatory diseases > Inflammatory bowel disease
Crohn's disease
Life Sciences > Health Sciences > Clinical Medicine > Diseases > Gastrointestinal Diseases > Inflammatory bowel disease > Crohn's disease
Artificial Intelligence
Mathematics and Computing > Computer Science > Artificial Intelligence
Natural Language Processing (NLP)
Mathematics and Computing > Computer Science > Artificial Intelligence > Natural Language Processing (NLP)
Computed Tomography
Life Sciences > Health Sciences > Health Care > Medical Physics > Medical Imaging > Radiography > Tomography > Computed Tomography
Computer Vision
Mathematics and Computing > Computer Science > Computer Imaging, Vision, Pattern Recognition and Graphics > Computer Vision
  • npj Digital Medicine npj Digital Medicine

    An online open-access journal dedicated to publishing research in all aspects of digital medicine, including the clinical application and implementation of digital and mobile technologies, virtual healthcare, and novel applications of artificial intelligence and informatics.

Related Collections

With collections, you can get published faster and increase your visibility.

Artificial Intelligence in Emergency and Critical Care Medicine

This Collection focuses on the unique challenges and opportunities for artificial intelligence (AI) applications in the emergency department (ED) and intensive care unit (ICU), environments where rapid decision-making and precision are critical to patient survival. These settings are characterized by their fast pace, high patient turnover, unpredictable workloads, and the need to manage acute and life-threatening conditions.

Publishing Model: Open Access

Deadline: Oct 10, 2025

Digital Health Equity and Access

This Collection explores innovations and challenges in advancing digital health equity and access, focusing on diverse populations and inclusive technologies.

Publishing Model: Open Access

Deadline: Sep 03, 2025