Discover AI models, datasets, platforms, and computational tools advancing research across the Commonwealth.
Applied research projects across healthcare, agriculture, public health, and education.
smell-datasets Unless otherwise noted, this work is derived from the Institute for Biomedical Informatics Innovation Core at the University of Kentucky. Introduction Electronic nose (e-nose) technology is a type of…
AI-powered patient-to-clinical-trial matching using reasoning models for eligibility decisions.
Endoscopy 3D Depth Visualization Interactive 3D depth-surface visualizations of endoscopy images and video, viewable in any browser. Two scripts, each producing a self-contained Plotly HTML file you can rotate, zoom,…
UAV World Model PLAN — Predictive Latent Autonomous Navigation. Imagination beats detection for drone danger. A world model that rolls its latent forward sees a threat a single-frame detector can't,…
The Academic Foundation Model Index (AFMI) An index of foundation models trained natively, from scratch, on their own data and tokenizer, by academic and research institutions. Universities come first; research…
<div align="center"> 🤖 Free Claude Code Use Claude Code CLI, Codex CLI, their VS Code extensions, JetBrains ACP, or chat bots through your own provider-backed proxy. Free Claude Code routes…
Pre-trained and fine-tuned models for computer vision, NLP, and medical AI.
Model Card for Neuropathology Vision Transformer: NP-GIANT This model is a Vision Transformer adapted for neuropathology tasks, developed using data from the University of Kentucky. It leverages principles from self-supervised…
Model Card for Finetuned-DINOv2-Chest-CT This repository hosts the backbone weights for a foundational Vision Transformer (ViT-Large with Registers) fine-tuned on Chest CT scans using the self-supervised DINOv2 algorithm (incorporating iBOT…
Variants: Kentucky-Open-Science/KOS-V4-Instruct, Kentucky-Open-Science/KOS-V4-Instruct-GGUF (GGUF), Kentucky-Open-Science/KOS-V4-Base license: cc-by-nc-sa-4.0 library_name: transformers pipeline_tag: text-generation language: en tags: clinical medical instruction-following tool-calling function-calling KOS-V4 from-scratch <div align="center"> <img src="scratch_llm.png" alt="Scratch LLM" width="400"/> </div> Code…
Curated datasets for training and evaluation.
Peer-reviewed papers and preprints from Kentucky researchers.
Abstract Nontuberculous mycobacteria (NTM) are ubiquitous bacteria that cause a spectrum of diseases, most notably pulmonary disease (NTMPD). The host factors contributing to the heightened susceptibility and severity of NTMPD…
Abstract Alzheimer's disease neuropathological changes (ADNC)-operationalized with semi-quantitative parameters-represent the consensus-based gold standard for diagnostic evaluation of disease severity. Although useful, ADNC diagnostic frameworks have limitations, particularly in advanced disease…
Abstract Coronary artery calcium (CAC) scoring is a key predictor of cardiovascular risk, but it relies on ECG-gated CT scans, restricting its use to specialized cardiac imaging settings. We introduce…
Abstract Automated radiology report generation from 3D computed tomography (CT) volumes is challenging due to extreme sequence lengths, severe class imbalance, and the tendency of large language models (LLMs) to…
Abstract Coronary artery disease (CAD), one of the leading causes of mortality worldwide, necessitates effective risk assessment strategies, with coronary artery calcium (CAC) scoring via computed tomography (CT) being a…
Abstract Histopathological image analysis plays a critical role in modern medical diagnostics, particularly in the detection and classification of various types of cancer. This study proposes a method called HistoDARE…
Federal and institutional grants supporting Kentucky research.
Agency: NIH/NIDAAward Number: 1U54DA058256-01Program: AppalTRuST Project 3
Agency: NSFAward Number: OCI-1246332
Agency: NIH/HHSAward Number: R01 DK124774
Expanding access to AI training resources across Kentucky through the NAIRR pilot program.
Self-service tools for researchers — no programming expertise required.
Secure, web-based AI transcription platform with speaker diarization, timestamping, and LLM-powered analysis.
No-code, web-based machine learning platform for training and evaluating classification models on tabular data.
User-friendly web platform for time series forecasting with multiple models and LLM-assisted interpretation.
Self-service platform for interacting with open-source large language models via web chat interface or OpenAI-compatible API.
Open-source automated protocol adherence platform using finite state machines and conversational AI for clinical research.
Platform for training and deploying foundational vision AI models using self-supervised learning on Vision Transformers.