Mediscale aims to provide physicians with the best medical decision support systems that will allow them to get the most comprehensive, effective, and actionable analyses of their patients’ status.
Today's experienced clinician needs close to 2 million pieces of information to practice medicine and doctors subscribe to an average of seven journals, representing over 2,500 new articles each year, making it almost impossible to keep abreast with the latest information about diagnosis, prognosis, therapy and related health issues.
Furthermore, the interpretation of patient data is difficult and complicated, mainly because the required expert knowledge in each of many different medical fields is enormous and the information available for the individual patient is multi-disciplinary, imprecise and very often incomplete.
Mediscale Prenatal Screener is an evidence-based decision support system that provides quick and comprehensive multi-factor paDent-data analysis. It presents the OB/GYN practitioner with real-time risk assessments, in-depth actionable recommendation, and clear follow-up suggestions.
Prenatal Screener uses routine tests performance during the pregnancy to provide the OB/GYN with a full analysis of geneDc, chromosomal, neurological, and developmental fetal anomalies.
Mediscale Prenatal Screener operates according to a versatile, multi disciplinary model that is being constantly updated with the latest relevant medical research. PrenatalScreener’s vast knowledge-base is designed to take hundreds of the pa5ent’s data markers and cross-reference them with thousands of rules and tens of thousands of permuta5ons, all in real-time. The analyzed data is displayed verbally and visually for fast and easy interpretation by physicians.
Mediscale Prenatal Screener is designed to fit perfectly into an organization’s information systems, by communicating with existing EMR systems and retrieving relevant parents’ information.
With assistance from the Founders team members, Mediscale successfully designed and developed the ML modules responsible for securely managing patient data streams. These modules analyze, cross-reference, and provide real-time risk analysis along with a set of recommendations.