Unlocking Clinical Data Efficiency: A Co-Authored Poster by MEDSIR, Virgen del Rocío University Hospital and Science4Tech at AIME 2024 

clinical data

Science4Tech is honored to announce the abstract  “Evaluation of a Generative Artificial Intelligence (AI) and Natural Language Processing (NLP) tool to obtain clinical data from electronic health records (EHRs) versus manual data capture in Oncology Clinical Trials: The MIRROR study”  has been accepted for a poster presentation at the prestigious 22nd International Conference on Artificial Intelligence in Medicine (AIME 2024) in Salt Lake City, Utah (July 9-12). AIME brings together leading AI and healthcare researchers.

This acceptance marks a major milestone for Science4Tech, highlighting CapTrial‘s potential to revolutionize how clinical data is captured, structured, and contextualized to get faster insights and adapt clinical trials in real-time. 

The MIRROR Study: A Joint Effort to Advance Clinical Research

The accepted abstract details the findings from the MIRROR study, a joint effort between MEDSIR, Virgen del Rocío University Hospital and Science4Tech that evaluated CapTrial’s effectiveness in extracting clinical data from electronic health records (EHRs) compared to traditional manual data capture methods. The study leveraged electronic Case Report Form (eCRF) data, considered the gold standard for clinical trials, from 11 oncology trials sponsored by MEDSIR and carried out at the Virgen del Rocío University Hospital. This data was then compared to EHR data automatically extracted by CapTrial©.  

The results of this collaborative study will be presented in a poster format at AIME 2024, offering valuable insights into the accuracy and efficiency of CapTrial© for streamlining data collection within the clinical research landscape.

CapTrial©: Pioneering AI for Streamlined Clinical Research

CapTrial© leverages the power of GenAI and NLP to automate data extraction from EHRs. This innovative approach has the potential to significantly improve the efficiency and accuracy of clinical trials. By streamlining data collection, CapTrial© can lead to faster trial completion times, reduced costs, and ultimately, accelerate clinical research.  

We at Science4Tech, along with our valued collaborators, are excited to share these groundbreaking findings with the AI and medical research community at AIME 2024. This acceptance signifies a crucial step forward in our commitment to revolutionize clinical research through the power of AI.