OFweekRobotA few days ago, the medical artificial intelligence company Peptide Building Block Technology officially released the medical image-assisted diagnosis Robot and the medical big data artificial intelligence training platform, and announced that it has received millions of angel investment from a pharmaceutical group.
Founded in 2016, Peptide Blocks is committed to combining deep learning with medical care to provide a full chain of artificial intelligence services. Based on artificial intelligence technology represented by deep learning, Peptide Building Blocks has launched an artificial intelligence-assisted medical image reading platform and built a medical big data artificial intelligence training platform, which is open to doctors to help the formation and breakthrough of scientific research results, and promote artificial intelligence technology in Rapid popularization and expansion in the medical field.
Medical imaging diagnostic Robot: low-cost and high-efficiency auxiliary reading tool for different medical institutions, using artificial intelligence technology, can achieve second-level accurate reading, and can realize disease diagnosis, grading diagnosis, lesion identification, and automatic case generation based on image conclusions , treatment plan recommendations and disease development prediction and other whole-link diagnosis and treatment assistance work.
●Medical big data artificial intelligence training platform: It includes four modules: data integration and cleaning, labeling platform labeling, rapid robot training, and standard interface application. While achieving high-quality collection of medical images and labeling data, it can be opened to practitioners to label data and train it into a robot for assisting diagnosis to assist in the formation of scientific research results.
Peptide building blocks are the first to apply deep network to lesion identification and marking and disease course judgment. The original LP-NET operator has a strong ability to extract local information, especially in the identification of small early lesions. Starting from the reading and recognition of fundus photos, Peptide Blocks combines traditional image processing methods with cutting-edge deep learning technology. On the test set, the highest accuracy rate has reached 97%, and the stable accuracy rate has reached 91%. The lesion marking of a fundus image can be completed within 13 to 15 seconds, and it also has good generalization ability. Through cooperation with primary hospitals, Peptide Building Blocks has accumulated more than 300,000 standard medical images, including fundus photos, X-rays, CT and deep desensitization diagnosis results. In the next step, Peptide Blocks will apply AI-assisted diagnosis technology to more fields such as X-ray chest X-ray and chest CT.
In addition to the engineering and productization of medical artificial intelligence technology, Peptide Building Blocks also actively participates in cutting-edge medical scientific research in conjunction with tertiary hospitals. ), Guangzhou Provincial Hospital and other 9 tertiary hospitals have reached strategic cooperation in ophthalmic artificial intelligence, and cooperated with more than 20 grassroots hospitals in the implementation of data and products.
Ms. Bo Wenjie, the founder of Peptide Building Blocks, recently conducted academic cooperation and exchanges on the combination of glaucoma and AI at the Sun Yat-Sen University Zhongshan Ophthalmic Center Glaucoma Center with Deputy Director Prof. Fan Zhigang and Johns Hopkins Ophthalmic Center Prof. Michael Boland. On the other hand, it discusses the construction mode of foreign multi-center data platform, the current situation and development direction of cross-center academic cooperation. In addition, the three parties also discussed in depth the application of AI in the diagnosis and management of glaucoma, and how it can be applied to multiple key links such as early screening and postoperative follow-up.
Regarding the millions of angel investment obtained, Bai Wenjie said that the funds will be mainly invested in technology and product research and development, and at the same time, it will be quickly brought to the market, so that artificial intelligence technology can better help more doctors and patients.
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