MiCRC is a project that uses artificial intelligence to support the early detection of colorectal cancer through the analysis of microbiome data. By studying the composition of microorganisms in a simple fecal sample, the system helps identify individuals at higher risk of colorectal cancer or pre-cancerous lesions which supports earlier and more targeted diagnosis.

Problem

Colorectal cancer is one of the leading causes of cancer-related deaths worldwide. Detecting the disease at an early stage is critical to improving survival rates and reducing healthcare costs. However, many current screening methods are invasive, expensive and can result in unnecessary procedures, including follow-up colonoscopies, increasing the burden on both patients and healthcare systems. This creates a strong need for accurate, less invasive tools that can better identify which patients require further clinical examination.

Solution

Artificial intelligence is used to analyze the microbiome composition obtained from a fecal sample. After its collection with a standard device, microbial DNA is sequenced to create a detailed microbiome profile. AI models then identify patterns associated with colorectal cancer risk, detecting individuals who may have tumors or high-risk pre-cancerous lesions. Based on this risk assessment, a colonoscopy is recommended only when necessary, enabling more targeted, efficient and less invasive screening.