Can a new generation of artificial intelligence set off the industrial revolution? This is not only a problem for AI development companies, but also a concern for beneficiaries of AI technologies such as doctors and patients. On the afternoon of April 12th, Tongdu Capital hosted the 12th salon of Tongdu Time, co-organized by Arterial Network and Tsinghua School of Economics and Management, “Where is the ' Medical + AI' Road?†The application value and commercialization of a new generation of artificial intelligence in the medical field The potential has entered an in-depth discussion. This meeting invited Song Sen, a professor of biomedical engineering and brain-like research center of Tsinghua University; a professor of Shanghai First Maternal and Infant Health Hospital, and a founder of Chuntian Medical Management; Mr. Li Yiming, co-founder of Shenrui Medical; Li Xing; Li Xiaodong, co-founder of Lianxin Medical; Zhang Dadi, partner of Danhua Capital; Fei Xiaotong, chief engineer of Xuanwu Hospital Information Center, and Yu Hui, partner of CLP Health Fund, as guests of the salon. At the same time, many industry experts, investors and entrepreneurs participated in the event. "Medical + AI" should go where to go, let us find the answer together from the content of the meeting. Image examination is the most common means for patients to go to the hospital for examination. At this stage, medical imaging equipment is very popular. Now, 80% of clinical treatment requires prior CT and MRI examinations. The data produced by these devices is standardized and very easy to handle. But in daily work, radiologists typically spend a lot of time browsing medical images. The browsing process of each image is generally only about five minutes, and repeated browsing and recognition for a long time will reduce the accuracy of the doctor, so misdiagnosis sometimes occurs. Li Yiming, co-founder of Shenrui Medical, pointed out at the meeting: "In today's medical system, we do not have enough resources to support a large number of high-quality medical resources. This is the opportunity of 'medical + AI', to make up for the current through AI. A huge gap. Shenrui Medical uses medical images as an entry point to slowly discover the value of 'Medical + AI'." Many doctors are reluctant to put their energy into the inspection of healthy people. They still can't provide timely services to the sick people, and they have no time to serve healthy people. Taking the CT of the lung as an example, if the CT is required at the outpatient clinic, the doctor will often do very detailed. However, if the CT is performed during the physical examination, the doctor may not take time to browse carefully. As a result, small lesions are easily overlooked. Detection of pulmonary nodules (picture from Shen Rui Medical) AI technology can exert great effects in the field of image. On the one hand, image data structure standards, large amount of data, easy to learn AI; on the other hand, AI does not feel sleepy due to repeated labor, even if AI diagnoses images incorrectly Judgment, but the actual false positive rate is far lower than the radiologist. AI can free doctors from repeated low-level labor liberation and let doctors do more meaningful things. In the future, patients need humanistic care, which is impossible for cold machines. There are three problems with medical information: incomplete, inaccurate, and unstructured. Duan Tao, the founder of Chunyu Medical Management, talked about the issue of medical information at this meeting. He believes that the root cause of the above problems in medical information comes from insufficient medical resources, and too few high-quality medical resources bear too much burden. Although the Health and Welfare Committee has distributed enough forms to collect information from doctors, doctors are always in a state of high-load work, and even work can not cope, how to spend time to organize medical data? This led the doctor to perfunctory the corresponding form, the form lost its meaning, and the collected data was also incomplete and useless data. AI can solve this problem from both indirect and direct ways. On the one hand, AI can directly analyze the condition and determine the physical condition of the patient. In this case, AI requires two types of data—the patient's genotypic data and phenotypic data. The hospital can give the patient's case to the AI ​​in advance, and the AI ​​can determine the condition after receiving the genotype data and then accepting the phenotypic data obtained by the patient or the doctor's personal visit. In this case, the doctor can save a lot of time, and the confirmed data is also standardized, structured, complete and accurate. In this way, AI can release the doctor's time and solve the pain points of medical data. AI-assisted analysis must have a false positive rate, but we must have enough patience with the machine, because even a senior doctor will misjudge for various reasons. According to Dr. Duan Tao, an experiment in 2017 showed that an AI system defeated 95% of doctors in analyzing the condition. On the other hand, AI can label and analyze data such as images; automate the processing of information generated by medical devices; organize and analyze big data according to algorithms, these functions will reduce the burden on doctors, and doctors have more energy to analyze Some data that AI can't handle indirectly solve the pain points of the above medical information. Insulin Syringes Needle,Disable Syringe,Monoject Syringe,10 Ml Syringe FOSHAN PHARMA CO., LTD. , https://www.foshanpharma.com