Webiomed

Webiomed, developed by K-SkAI LLC, is an AI-enabled predictive analytics and risk assessment platform designed specifically for healthcare organizations. This innovative solution utilizes machine learning algorithms to analyze large volumes of medical data, extract relevant information from electronic medical records, and identify patterns and risk factors. Webiomed caters to a wide range of healthcare professionals, medical researchers, healthcare administrators, data analysts, and pharmaceutical companies, making it a valuable tool across various professions and industries within the healthcare sector.

Key Features

Predictive Analytics: Webiomed utilizes machine learning algorithms to provide predictive analytics in healthcare. It autonomously interprets information from medical data, extracts relevant data from electronic medical records, and identifies trends and risk factors, enabling accurate forecasting of health events.

Risk Assessment: Webiomed conducts comprehensive risk assessments based on the analysis of de-identified medical data. It identifies risk factors and forecasts the development of diseases, allowing healthcare professionals to proactively manage patient health and mitigate potential risks.

Clinical Decision Support System: Webiomed serves as a clinical decision support system by providing accurate and autonomous interpretation of medical information. It compares current data with historical data, evaluates health indicator dynamics, and identifies potential risks, empowering healthcare professionals to make informed decisions.

Feature Extraction from Unstructured Medical Records: Webiomed utilizes natural language processing (NLP) algorithms to extract features from unstructured medical records. It identifies and extracts symptoms, blood pressure data, patient height and weight, lab test results, and other relevant information, transforming unstructured data into structured data for analysis and decision-making.

Machine Learning Models: Webiomed offers various machine learning models, including predictive analytics models for forecasting health events. It provides models for extracting features from text records and identifying suspected diseases. The platform enables direct API access to its machine learning models, facilitating integration with other systems.

Real-World Data Analysis: Webiomed collects, analyzes, and utilizes real-world data (RWD) from electronic health records. It incorporates demographic and geographic data, healthcare facility information, and health system indicators to support research, analysis, and decision-making in healthcare.

Integration Service: Webiomed provides an integration service that ensures seamless interaction with external information systems through its standard API. It facilitates the integration of Webiomed with other healthcare information systems, enabling efficient data exchange and interoperability.

Research Projects: Webiomed actively participates in scientific research and development in the field of artificial intelligence. The platform collaborates on grants, publications, and conferences to contribute to the advancement of AI in healthcare, ensuring it stays at the forefront of research and innovation in the industry.

Data Set Creation: Webiomed accumulates de-identified data from medical records and creates datasets for machine learning and research purposes. It extracts and structures data to facilitate machine learning model development and analysis, contributing to the creation of valuable datasets for research and development in healthcare.