Nucleati's AI: Revolutionizing Evidence-Based Medicine with Evidence Collection and Entity Extraction

Artificial intelligence (AI) has the potential to revolutionize the field of medicine, and evidence-based medicine is no exception. While limited sources of reliable evidence have been a major challenge in the past, advances in natural language processing technology are making it possible to scale up the evidence collection and documentation process, even in the absence of large numbers of experts in the field.

Nucleati works closely with healthcare organizations and researchers to leverage AI for evidence collection and entity extraction. The primary reason for limited sources of reliable evidence is the scalability of the evidence collection and documentation process. However, with advances in AI, sub-tasks of evidence-based medicine, such as identifying relevant literature, extracting entities, and summarization, can now be automated to a certain extent, allowing the evidence-based medicine process to be scaled up more effectively.

To develop and implement AI models for evidence collection and entity extraction, Nucleati works with clients to develop a high-quality training, validation, and test database. Next-generation tools are used to build AI models that can accurately identify and extract relevant entities from large volumes of medical literature. The performance and capabilities of the models are transparently communicated to clients, who can then integrate them into their workflow or use them as independent applications.