Synthetic & Artificial Medical Cadavers and Data Analytics

Artificial Medical Cadavers & Data Analytics is a service that caters to medical organizations, teaching hospitals, universities, and colleges. Our Data Analytics service works with research organizations, scholars, and professors to provide them with decision-making insight on the success of a specific initiative, simulator, or symptoms that they would like to introduce to their students or learners or integrate into decision-making exercises while selecting, working with sources such as Electronic Health Records (EHRS), Personal Health Records (PHRs), Electronic Prescription Services (E-Prescribing), Patient Portals, Master Patient Indexes (MPI), Health Related Smart Apps, and more.
Artificial Medical Cadavers service is a mix of hardware and software combination. This service integrates Artificial Intelligence into Synthetic cadavers and makes them available for medical students for Open cadaver, open body learning experience with symptoms and illness for real-life experience.

Synthetic & Artificial Medical Cadavers and Data Analytics:


Artificial medical Cadavers are also known as Synthetic Cadavers. These are head to tow replicas of the human body, from fat tissue to elastic tendons and ligaments to organs and rigid bones. MDX Technologies utilizes Artificial Intelligence with Machine Learning technology to create various illnesses and integrate them into these cadavers.

We integrate small circuits, mechatronics, and other technologies with AI and ML-based programs to create various functions, from a beating heart to simulated childbirth in a cadaver, and turn it into an intelligent cadaver for education, training, and research & development.
Data analytics examines raw datasets to find trends, draw conclusions and identify the potential for improvement. Healthcare analytics uses current and historical data to gain insights, macro and micro, and support decision-making at both the patient and business levels.

The use of health data analytics allows for improvements to patient care, faster and more accurate diagnoses, preventive measures, more personalized treatment, and more informed decision-making during the complete lifecycle of a patient from Admittance to Release.