Biomedica's X1 Imaging is an AI-based tool for comprehensive medical image recognition. The software offers a range of functional modules to accommodate image import, AI labeling and training, AI model management, and more. Capable of supporting multiple medical image formats, X1 Imaging can process large image data of billions of pixels without difficulty. The tool offers the functionality to train AI models or load pre-trained models for analysis. With the ability to integrate fully with Biomedica's PatientSense, the software aids in creating and maintaining complete patient information. A distinctive feature of the technology is its capability for low-resource computing, enabling AI training even with lesser data.

Biomedica's Osteoporosis AI Screening Assistant employs proprietary AI models to conduct a detailed analysis of bone health in a blink of just six seconds. With an impressive accuracy rate of 90%, this pioneering tool can be utilized in clinics and health check-up centers for quick and precise osteoporosis screening. It has the potential to bridge the gap in osteoporosis screening, aiding in early detection of potential risks. The kit supports multiple image formats, including DICOM, jpg, and jpeg, and can handle billions of pixels images and performs with low-resource computing.

Biomedica's Leukemia AI Screening Assistant is a cutting-edge solution designed to help physicians and lab technicians efficiently classify cell types of bone marrow smears. In the face of increased healthcare demand due to rising life expectancies, this tool serves to improve analysis efficiency and decrease the false negative rate. It can further enhance its effectiveness when used in tandem with PatientSense by integrating data analysis and case data for more effectively implemented and managed diagnoses, care, and tracking. The solution supports various microscope brands including Zeiss, Leica, and Olympus, among others.

Biomedica's Cervical Cancer AI Screening Assistant is designed to improve the precision and efficiency of cancer screening. Geared towards assisting clinical medical laboratory scientists, this tool can accurately identify specimens with abnormal lesions, reducing the false negative rate of slide reading. By optimizing the slide reading process, it enables a greater number of women to undergo Pap smears, alleviating strain on medical testing units and enhancing the standard of healthcare. It supports multiple microscope brands and aims to be employed in markets worldwide to advance women’s health.