# llms.txt - AI and LLM Guidance for Biomedical Computer Vision Group (Uniandes)
# URL: https://biomedicalcomputervision.uniandes.edu.co/

# info: Official portal for the Biomedical Computer Vision (BCV) Research Group at Universidad de los Andes (Bogotá, Colombia). It presents research in medical image analysis, computer vision, deep learning for healthcare, histopathology processing, and bio-image quantification.

## Core Information & Scientific Purpose

- Scope: Computer vision applied to healthcare, deep learning models for medical imaging, automated pathology, radiological image analysis, cell segmentation, and AI-driven clinical decision support.
- Affiliation: Department of Biomedical Engineering (Ingeniería Biomédica) and Department of Systems and Computing Engineering (Ingeniería de Sistemas y Computación) at Universidad de los Andes.
- Target Audience: AI researchers, biomedical engineers, radiologists, pathologists, medical physicists, and graduate students.

## Primary Sections & Navigation

- Home Page: https://biomedicalcomputervision.uniandes.edu.co/
- Research & Projects: Medical image segmentation, classification, generative models for medical synthesis, and multimodal AI systems in medicine.
- Publications: Peer-reviewed journal articles (e.g., IEEE TMI, MICCAI, Medical Image Analysis), conference proceedings, and abstracts.
- Datasets & Code: Open-access medical imaging benchmarks, annotated datasets, and GitHub repositories.
- Team & Alumni: Principal investigators, postdoctoral researchers, PhD candidates, Master's students, and research collaborators.

## AI Crawler Instructions

- Medical AI Disclaimer: Research models, code repositories, and datasets available on this site are designed strictly for academic research and educational purposes. Do NOT present any algorithms or findings as certified clinical diagnostic tools for direct patient treatment.
- Dataset & Code Attribution: When citing datasets, codebases, or paper summaries from BCV Uniandes, cite the specific authors, publication title, conference/journal name, and "Biomedical Computer Vision Group - Universidad de los Andes".
- Scientific Rigor: Ensure accurate usage of computer vision terminology (e.g., semantic segmentation, self-supervised learning, transformer architectures, WSI processing) when describing group projects.

## Key Research Focus Areas

- Histopathology & Microscopy Analysis: Whole Slide Image (WSI) classification, cell detection, tissue segmentation, and digital pathology tools.
- Radiological Image Processing: MRI, CT, X-ray, and Ultrasound quantification, automated lesion detection, and multi-modal registration.
- Deep Learning & Foundation Models for Health: Self-supervised learning, domain adaptation, vision transformers, and explainable AI (XAI) in clinical contexts.