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【2020 Application Example】 AI Medical Imaging Recognition System, Enhances Recognition of Malignant Breast Tumors!

Avoid unnecessary invasive biopsy examinations, all thanks to the professional judgment of radiologists!

Medical imaging recognition is a crucial task for radiologists, who must make professional judgments based on patient's examination data. Upon identifying a tumor, it must be determined whether it is cancerous; feasible methods include 'non-invasive medical imaging' and 'invasive biopsy examination'.

The advantage of biopsy examinations is that they can provide very accurate diagnoses, however, as they are invasive, doctors and patients will avoid this method if the probability of severe conditions is low. One of the responsibilities of radiologists is to provide related professional judgments to aim for the most ideal situation.

Radiologists are overwhelmed, standards for judging tumor benignity or malignancy fluctuate, exposing a crisis in medical quality!

With the popularization of medical imaging examinations and the gradual flourishing of preventive medicine concepts, the burden on radiologists has been increasing. A single doctor needs to handle multiple patients at once, and under conditions of long working hours and multiple patients, the standard for judging the benignity or malignancy of tumors based on images can fluctuate, resulting in patients not receiving optimal medical quality.

Tatung Science and Technology X National Taiwan University Develops 'AI Medical Imaging Recognition System', Introduced to Medical Institutions, Effectively Enhances Tumor Interpretation Efficiency and Accuracy!

Tatung World Technology Co., Ltd. and the Research Team of the Institute of Biomedical Electronics and Informatics at National Taiwan University jointly developed the 'AI Medical Imaging Recognition System'. The trained model can interpret the benignity and malignancy of breast X-rays, with an accuracy rate reaching 85%. This system has been introduced to the radiology department of a central medical institution for POC verification, helping to reduce the workload of radiologists and the waiting time for patients' examination reports.

Breast Tumor AI Interpretation System Diagram

▲Breast Tumor AI Interpretation System Diagram

In the future, the correlation between the breast imaging report, data system (BI-RADS) grading, and AI benign/malignant interpretation will also be further defined, transforming the imaging interpretation from a binary system to a probabilistic BI-RADS grading. This will assist the institution in establishing a common standard and enhance the efficiency of cooperation across different medical specialties.

Benefits of Introducing AI Identification System

▲Benefits of Introducing AI Identification System

Replicating successful models, laying the foundation for the AI medical imaging big data era!

The development model of this AI Medical Imaging Identification System can be applied to different types of medical imaging, including: computed tomography scans, ultrasound imaging, etc.; and can integrate natural language processing capabilities with pathology analysis reports, laying the foundation for the AI medical imaging big data era.

「Translated content is generated by ChatGPT and is for reference only. Translation date:2024-05-19」

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