Process up to 7 M chars per hour for real-time and up to 35 M chars per hour for batch mode.

This model is an efficient solution for the automatic detection and classification of risk factors in patient histories and clinical notes. It utilizes cutting-edge natural language processing techniques to accurately identify risk factors like Diabetes, Hypertension, Obesity, and Smoking, among others. It is tailored to meet the needs of healthcare professionals, clinicians, and medical researchers, providing them with a reliable tool for extracting vital risk factors from various medical documents.

Key Features:

• Efficiently identifies a wide array of risk factors, including Coronary Artery Disease, Diabetes, Family History, and more, ensuring comprehensive patient risk profiling.
• Supports preventive care strategies by providing accurate risk factor detection, aiding in early intervention and management.
• Facilitates evidence-based clinical decision-making by delivering precise information on patient risk factors.
• Enhances patient profiling and healthcare planning by offering high-accuracy data extraction from clinical narratives.

This model is invaluable in the healthcare sector, offering a robust tool for clinicians and researchers to optimize patient care and preventive strategies. It ensures precise risk factor identification, contributing to better patient outcomes and informed clinical decision-making. Covered entities: CAD, DIABETES, FAMILY_HIST, HYPERLIPIDEMIA, HYPERTENSION, MEDICATION, OBESE, PHI, SMOKER.