首页|Great Ormond Street Hospital for Children NHS Foundation Trust Reports Findings in Artificial Intelligence (Facilitating the use of routine data to evaluate art ificial intelligence solutions: lessons from the NIHR/RCR data curation workshop )
Great Ormond Street Hospital for Children NHS Foundation Trust Reports Findings in Artificial Intelligence (Facilitating the use of routine data to evaluate art ificial intelligence solutions: lessons from the NIHR/RCR data curation workshop )
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Artificial Intelligenc e is the subject of a report. According to news reporting out of London, United Kingdom, by NewsRx editors, research stated, “Radiology currently stands at the forefront of artificial intelligence (AI) development and deployment over many o ther medical subspecialities within the scope of both research and clinical prac tice. Given this current leadership position, it is imperative that we foster co llaboration and knowledge sharing to ensure the ethical, responsible and effecti ve continued progress of AI technologies in our field, ultimately leading to enh anced patient care.” Our news journalists obtained a quote from the research from Great Ormond Street Hospital for Children NHS Foundation Trust, “To achieve this objective, three w orkshops have been planned through a coordinated effort by the NIHR/RCR committe e. These workshops aim to convene key stakeholders including eminent academics, departmental leaders and industry partners to provide insights from their own ex periences and strategies to overcome common challenges faced. In this article, w e describe the outcomes from the first workshop, which addresses the topic of ‘f acilitating the use of routine data to evaluate AI solutions’. The main key insi ghts uncovered include the need for ethical considerations, detailing of methods for data curation and storage depending on the need and requirements for de-ide ntification. We provide resources for how to de-identify data and also a list of concerns to think about before curating your data.”
LondonUnited KingdomEuropeArtifici al IntelligenceEmerging TechnologiesMachine Learning
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