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Using John Snow Labs’ Medical Large Language Models on Azure Fabric

John Snow Labs

John Snow Labs’ Medical Language Models library is an excellent choice for leveraging the power of large language models (LLM) and natural language processing (NLP) in Azure Fabric due to its seamless integration, scalability, and state-of-the-art accuracy on medical tasks.

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Predictive analytics helps Fresenius anticipate dialysis complications

CIO

German healthcare company Fresenius Medical Care, which specializes in providing kidney dialysis services, is using a combination of near real-time IoT data and clinical data to predict one of the most common complications of the procedure. “IDH Hemodialysis is a life-saving treatment for those suffering from kidney failure.

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Healthcare organizations must create a strong data foundation to fully benefit from generative AI

CIO

Since the introduction of ChatGPT, the healthcare industry has been fascinated by the potential of AI models to generate new content. While the average person might be awed by how AI can create new images or re-imagine voices, healthcare is focused on how large language models can be used in their organizations.

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MLOps: Methods and Tools of DevOps for Machine Learning

Altexsoft

When speaking of machine learning, we typically discuss data preparation or model building. Living in the shadow, this stage, according to the recent study , eats up 25 percent of data scientists time. MLOps lies at the confluence of ML, data engineering, and DevOps. Better user experience.

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Beyond the hype: 4 use cases that show what’s actually working with gen AI

CIO

Weve also seen some significant benefits in leveraging it for productivity in data engineering processes, such as generating data pipelines in a more efficient way. For example, companies can use data from their CRM systems to get data to create personalized communications. Well use Github for that.

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Harnessing Healthcare-Specific LLMs for Clinical Entity Extraction

John Snow Labs

Healthcare-specific language models, like the JSL-MedS-NER family, are designed to extract clinical entities from unstructured medical text. These models can identify key information such as clinical terms, drugs, side effect, cancer diagnoses, metastasis, and protected health information (PHI).

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Predibase exits stealth with a low-code platform for building AI models

TechCrunch

“The major challenges we see today in the industry are that machine learning projects tend to have elongated time-to-value and very low access across an organization. “Given these challenges, organizations today need to choose between two flawed approaches when it comes to developing machine learning. .