As Artificial Intelligence (AI) continues to revolutionize healthcare, one major challenge that has emerged is AI hallucinations in healthcare—situations where an AI system generates inaccurate or entirely fabricated information that can sound plausible but is not based on real data. While AI has shown immense potential in areas like diagnostics, clinical decision support, and patient […]
Sporo Health is thrilled to announce a significant milestone in the journey of integrating AI Agents within existing Electronic Medical Records (EMRs). Today, we welcome the SBXi Fund to our Sporo family. This partnership marks the beginning of a new era for Sporo Health, and we are excited to share this news with our community. […]
In today’s healthcare landscape, the security and management of Electronic Health Records (EHRs) are paramount. Sporo Health’s Advanced De-Identification Framework provides a robust solution for safeguarding sensitive patient data. This innovative framework, orchestrated by an AI agent, processes JSON data from EHR systems, ensuring that Protected Health Information (PHI) is securely de-identified and optimized for […]
In the evolving landscape of digital healthcare, leveraging AI-Agents to enhance patient-clinician interactions has become increasingly pivotal. At Sporo Health, we have developed an innovative product that generates insights, synopses, and various clinical notes from patient-clinician interviews. Utilizing an open-source, near real-time speech-to-text model for transcription, followed by a domain-specific language model (LLM) fine-tuned for […]
Sporo Health using AI Agents announced partnership with Microsoft.
The integration of AI agents in healthcare is revolutionizing the industry by automating complex workflows and enhancing efficiency. AI agents, powered by advanced machine learning algorithms, can process vast amounts of data to assist in diagnostics, treatment planning, and patient monitoring. In real-world applications, AI agents are already being used to analyse medical images, detect […]
