Real World Evidence

Transforming clinical research: Scaling real-world data across diseases with expert-led AI

June 20th, 2023|Categories: , , |Tags: , , |

The promise of improving patient care and outcomes through RWD has been understood for some time, but overcoming the fragmentation and inaccessibility of disparate data sources across disease states has proven to be a hard challenge across the industry. We’re not learning fast enough— this is where clinical expert-led AI can help. By using AI to standardize unprecedented volumes of data, uncover clinical details that have previously been hidden in free text notes, and represent full patient journeys in near real-time, researchers can ask and answer complex questions for targeted populations like never before.

Synthesise RWE and AI. Transform patient-driven healthcare

June 15th, 2023|Categories: , |Tags: , |

As the volume of the real word evidence data increases, the mechanisms to collect and translate the data into meaningful insights for pharmaceutical organisations becomes increasingly complex. Advances in technologies such as artificial technology have delivered global excitement, but mastering how to leverage AI for meaningful patient outcomes remains uncracked.

How to assess the quality of AI output when structuring unstructured medical data

May 26th, 2023|Categories: , , |Tags: , , |

Looking to empower your organizations with high quality patient data? Human abstraction has long been considered the gold standard for extracting high quality information from EHR data. With the rise of NLP, large language models, and machine learning, the question becomes: how should we evaluate these new technologies against the traditional abstraction methods?

  • Improving Patient Outcomes - AI-Based Phenotyping for Diagnosis, Treatment, and Clinical Trials

Improving Patient Outcomes: AI-Based Phenotyping for Diagnosis, Treatment, and Clinical Trials

April 28th, 2023|Categories: , , |Tags: , , |

Join a panel of OM1’s clinical experts in cardiometabolic disease, immunology, and mental health as they explore how Artificial Intelligence (AI) can find phenotypic patterns and unlock insights hidden in real-world data.

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