The scale of the problem we're addressing.
Global clinical screening data — breast cancer remains the most common cancer among women worldwide, where early detection is the single most decisive prognostic factor.
Early detection through regular mammography screening significantly improves survival rates. AI-assisted screening can identify subtle patterns in breast tissue that may be missed by the human eye.
Understanding breast cancer — and how we detect it.
Breast cancer develops when abnormal cells in the breast grow uncontrollably, forming tumors that can spread. It is the most frequently diagnosed cancer in women globally.
While risk factors include genetics, age, lifestyle, and hormonal influences, early detection through mammography remains the most effective tool for improving patient outcomes and reducing mortality. AiScan brings artificial intelligence to this critical moment.
Challenges vs. AiScan solution.
How our automated decision support system addresses traditional hurdles in mammography screening.
Variability in radiologists' experience may affect diagnostic consistency.
Delivers consistent, uniform automated analysis to support and align radiological assessments.
The increasing volume of mammography examinations places significant pressure on radiologists.
Dramatically reduces evaluation times by automatically flagging anomalies and pre-sorting cases.
Dense breast tissue and subtle lesions may be difficult to detect by visual assessment alone.
Employs pixel-level enhancement and pattern recognition to identify hidden lesions in dense tissue.
Many healthcare facilities still lack automated AI-assisted mammography analysis.
Functions as a digital second reader, providing malignancy risk calculations and automated diagnostic support.
Clinical workflow integration.
Transforming the mammography screening pipeline from hours to minutes using automated AI orchestration.
Manual Pipeline
AI-Enhanced Workflow
Research laboratory.
AiScan Lab develops artificial intelligence solutions for breast imaging and precision oncology. Our multidisciplinary team combines expertise in radiology, oncology, artificial intelligence, and medical image analysis.
Dataset Curation
Building diverse, annotated mammography datasets with clinical validation from medical institutions.
Model Training
Developing convolutional and transformer architectures optimized for medical imaging tasks.
Clinical Validation
Rigorous testing against radiologist benchmarks with retrospective and multi-center validation studies.
Regulatory Pathway
Preparing documentation for medical software certification and clinical deployment approval.
Deployment
Integration with hospital PACS systems and radiologist workflow platforms.
Continuous Learning
Feedback loops with radiologists to improve model accuracy and clinical utility over time.
Eight minds. One mission.
The multidisciplinary team behind AiScan — radiologists, oncologists, AI engineers, and professors united by a shared commitment to women's health.
Xodjibekov Marat Xudaykulovich
Chief Executive Officer of AiScan. Bringing decades of radiology expertise to guide the company's strategic direction.
Xodjibekova Yulduz Maratovna
Scientific Advisor to AiScan. Providing expert guidance on radiological standards and clinical validation protocols.
Polatova Djamila Shagayratovna
Scientific Adviser specializing in oncology. Ensuring AiScan's clinical relevance and alignment with cancer treatment pathways.
Xamdamov Rustam Xamdamovich
Chief Technology Officer. Leading the technical architecture and infrastructure of the AiScan platform.
Turaqulov Shoxrux Xudayarovich
Software Developer focused on building scalable AI systems and platform infrastructure.
Pattaxov Aziz Shuhrat o'g'li
Data Analyst at AiScan. Bridging clinical expertise with data science to improve model accuracy.
Advancing early detection through innovation.
Connecting clinicians, researchers, and engineers to make AI-assisted screening accessible, rapid, and precise.