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Medical AI Applications Blog

This session introduces ‘CC’, the vCare Companion Robot, which helps hospital staff reduce administrative burden by 3+ hours per shift – and increase the quality of life for overburdened care staff. This is achieved using ambient listening to patient‑staff conversations for charting, reporting, vitals collection, and integration with electronic healthcare records at the point of care. Care staff no longer need to struggle with multiple devices to bring into the patient’s room: The ‘CC’ robot autonomously follows the care staff worker with the necessary tools, listens to conversations, automatically fills in forms, and integrates with EMR’s – thus freeing up hands and time to focus on the patient and care delivery. John Snow Labs’ Medical Language Models are used for ambient listening, speech‑to‑text, clinical information extraction and normalization, and automated filling of medical forms. The presentation will highlight lessons learned from developing this system at one of the US’s largest not‑for‑profit Life Care organizations.

Blog

This session introduces ‘CC’, the vCare Companion Robot, which helps hospital staff reduce administrative burden by 3+ hours per shift – and increase the quality of life for overburdened care...

Healthcare providers are increasingly required to adhere to guidelines and performance measures in order to comply with quality initiative, pay for performance, and payer standards. However, in practice many providers just...

Clinical reviewers frequently face the challenge of adapting to diverse data sources and formats. To address this issue, Evernorth has developed an innovative clinical support tool designed to facilitate rapid...

Functional and integrative medicine addresses complex, chronic health conditions by integrating vast datasets spanning genetics, microbiome analysis, metabolomics, environmental influences, and lifestyle factors. Unlike traditional medical algorithms, which are often...

Recent advancements in vision-language models (VLMs) have demonstrated remarkable capabilities across diverse domains. In this talk, we explore the effectiveness of VLMs in a transfer learning setting, where a pre-trained model...