Unlock hidden care gaps and maximize ROI with AI-powered patient journey analytics. Learn how integrating clinical and unstructured data identifies missed diagnoses, reduces readmissions, and streamlines coordinated care
Why analyze patient journey data? Patient journey data offers a holistic view of an individual’s healthcare experience, connecting clinical, behavioral, and operational touchpoints across time. When analyzed with AI, this...
What is a medical reasoning engine and how does it differ from search? Medical reasoning engines, powered by advanced large language models (LLMs), represent a new generation of clinical decision...
Designed from day one for secondary use of multimodal, longitudinal patient data, PJI embeds regulatory-grade governance and transparency into every patient journey. John Snow Labs, a healthcare AI company, today...
Oncology has always depended on multidisciplinary tumor boards (MTBs) to interpret complex, multimodal data, such as pathology reports, radiology findings, genomic profiles, prior treatments, patient history, and synthesize this information...
In our previous article, JSL Vision: State-of-the-Art Document Understanding on Your Hardware, we benchmarked JSL Vision against leading open-source vision-language models on FUNSD and OmniOCR In this follow-up, we address the natural next question...
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