{"id":840,"date":"2020-12-24T00:00:00","date_gmt":"2020-12-24T00:00:00","guid":{"rendered":"https:\/\/www.lunit.io\/media-hub\/ai-proves-its-value-in-assistance-for-emergency-cases-with-higher-accuracy-and-timely-reporting-time-of-chest-radiographs\/"},"modified":"2020-12-24T00:00:00","modified_gmt":"2020-12-24T00:00:00","slug":"ai-proves-its-value-in-assistance-for-emergency-cases-with-higher-accuracy-and-timely-reporting-time-of-chest-radiographs","status":"publish","type":"media-hub","link":"https:\/\/www.lunit.io\/en\/media-hub\/ai-proves-its-value-in-assistance-for-emergency-cases-with-higher-accuracy-and-timely-reporting-time-of-chest-radiographs\/","title":{"rendered":"AI Proves Its Value in Assistance for Emergency Cases-- With Higher Accuracy and Timely Reporting Time of Chest Radiographs"},"content":{"rendered":"

Lunit INSIGHT CXR reduces the waiting time for patients with its advanced reading and triaging, allowing better treatment and care<\/h2>\n

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A study shows that AI can individually mark abnormal findings for 10 lesions with significantly high accuracy<\/h3>\n

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A study conducted by Seoul National University Hospital, one of the most renowned medical institutes in Asia, has revealed that an AI can help radiologists improve their performance and reduce reporting time for critical or urgent cases. The study has recently been published in European Respiratory Journal, one of the leading peer-reviewed journals for respiratory diseases.<\/p>\n

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According to the study, Lunit INSIGHT CXR, an AI software for chest x-ray, showed significant value in a simulated reading experiment for emergency patients. When assisted by Lunit\u2019s AI, the diagnostic accuracy more than doubled from 29.2% to 70.8% for critical-emergency diseases such as pneumothorax and pneumoperitoneum.<\/p>\n

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\u25b2 Comparison of the urgency categorization accuracy between two reading sessions in the simulated reading test <\/p>\n<\/figcaption>

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In addition, by analyzing abnormal findings in advance and triaging the images for urgent diagnosis, the waiting time of emergency patients has been drastically reduced by 80%. The overall reading time has also shortened, leading to reading efficiency and dramatic improvement of patient treatment in emergency situations.<\/p>\n

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\u201cThis study actually shows that reading efficiency can be maximized when the radiologists and AI system are organically integrated,\u201d said Professor Chang-min Park, the corresponding author of the study. \u201cIt especially shows high value in emergency cases where timely diagnosis and care is required for patients.\"<\/p>\n

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Brandon Suh, CEO of Lunit said, \u201cIt is meaningful that our AI is recognized and validated for more sophisticated and quick diagnosis of chest diseases. Continuous development of our algorithm shall be implemented to reduce the heavy workloads of radiologists and emergency personnels.\u201d<\/p>\n

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\u25b2 Lunit INSIGHT CXR marks the location and probability of an abnormal finding on chest radiograph<\/p>\n<\/figcaption>

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The study further emphasized that Lunit INSIGHT CXR can detect 10 diseases (lung cancer, pulmonary nodules, atelectasis, calcification, cardiomegaly, consolidation, fibrosis, pleural effusion, pneumoperitoneum, and pneumothorax) on chest x-ray images. In fact, most lung and chest diseases can be diagnosed through this AI solution.<\/p>\n

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Using two external validation datasets of same-day CT-confirmed and open-source datasets, Lunit INSIGHT CXR showed diagnostic ability comparable to that of a radiologist. It resulted in high AUROCs for all 10 common abnormalities, ranging from 0.9-1.00. AUROC value of 1.00 implies the highest performance.<\/p>\n

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Professor Joo-gang Nam, the first author of the study stated \u201cLunit INSIGHT CXR individually marks the location and probability of abnormal findings for each of the 10 lesions. This is a technology that was not implemented in the previous generation of artificial intelligence, which opens the way for automatic detection and diagnosis.\u201d<\/p>\n

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Lunit INSIGHT CXR clinically analyzed more than 6.5 million images in more than 80 countries. It is CE marked and clinically available in Europe, Middle East, Latin America, South East Asia, Australia, and New Zealand. It is expecting its FDA clearance within early 2021.<\/p>\n

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