According to Forbes magazine, imagine that you receive a gift that will allow you to see the future. Imagine that if you look at someone, you can know that something bad is about to happen to them. You can also do something to prevent these bad things from happening. As a doctor, I (the author of this article, Ran Balicer, founding director of the Clalit Institute of Israel's Data Driven Health Innovation Center and consultant to the World Health Organization) wants to know: in a world where people can foresee the future, medicine What will happen to the health care sector? Maybe you don't have to go to the doctor again, but you will receive a call from the doctor one morning and tell you, "Hey, how are you this morning?" You would say "Great!" Then he replied: "Dear Please don't panic, but you will have a heart attack within 12 hours. So, come to the hospital and let us cure you before the symptoms appear." Is this not good? I know this sounds a bit like science fiction, but it is not. Israel has also made similar progress. Let us give a medical example of "preemptive strike". Your friend or family is undergoing dialysis treatment. You know how painful and debilitating this situation is. If we can identify the patient and get them out of danger before the symptoms start, it would be amazing! Early treatments are simple. Once there is pain and discomfort, it may be too late to treat because the kidneys have been severely damaged. In order to be able to seize the opportunity and proactively contact a seemingly healthy patient, you must predict which patient has a problem. Doctors use their years of experience to do this experiment, but the algorithm can make predictions more powerfully and efficiently. A few years ago, in Clalit, Israel's largest medical service provider (where I work), we used advanced analytics to build a predictive model that predicts who will be in 5 years after a seemingly healthy population. Go to the end of life during dialysis. The model was developed based on digital health data from more than half of Israel's population for decades, and includes approximately 4.5 million patients, usually from birth to old age. Then, we asked frontline doctors to lend a helping hand to these target groups, who are high-risk patients we have chosen. Our data show that after this preemptive intervention, the dialysis cases in this group have fallen dramatically. Previous work to prevent readmissions through smart predictions showed a 12% reduction in readmission rates after predictive interventions. We are doing the same thing now, trying to prevent diabetes, pneumonia, and even cancer, but it will take years to measure the impact. We can do these actions in Israel because there are decades of electronic medical records in our institutions and integrated data sets, strong economic incentives to keep patients healthy for a long time, and Israel prioritizes digital innovation in healthcare. . Here is an example of how an algorithm can predict the symptoms of human negligence. Recently we have worked with people to develop a model to predict who will develop osteoporotic fractures. For some reason, the algorithm insists that eye disease is an important part of these fracture predictions. Obviously, we think this is a glitch. I learned from medical school that there is nothing in common between eye diseases and fractures. We tried to fix the model, but the algorithm did not give up its analysis. Then it shocked us. Eye problems do not make the bones more brittle, but vision problems make the patient more likely to fall and therefore fracture. This is a key finding: in a large amount of data, computers outperform humans in acquiring so many subtle signals and patterns. These data can also be used to predict which treatments are most effective for which patients. But can drugs really be automated? Despite the risk of human error, or humans missing hidden signals and patterns, doctors still believe that they will always be better able to make the final judgment on the best state of the patient. But the world is constantly changing and medicine is changing. Today, doctors can benefit from the collective experience of millions of patients they have never seen before. Increasingly powerful computing power and advanced analytics, including machine learning and artificial intelligence tools, can scan large amounts of health data that spans geographic locations and even generations in huge repositories. They search for and find patients with similar symptoms and learn from their experiences, predict what will happen next, and develop the best course of action. This may be a near-perfect study group that matches you personally. Today we have a lot to do, imagine what happens when we add everyone's genes to this data, the match will be more precise, and the suggested treatments are tailored. On the one hand, human doctors have limited information storage and processing capabilities. The current situation is that there is too much data in a patient's medical record for the doctor to calculate, not to mention only 15 minutes of access time. There are too many things in the world that can be missed, and many things are missed every day. Predictive algorithms can search and identify patients, who are like sitting in front of a doctor, and doctors can determine the best treatment from their recorded experience. The more data fusion, the stronger the predictive power, and the more precise the treatment of personalized medicine. Dr. William Osler is one of the greatest doctors in history. He once said: "If it is not because of the huge differences between individuals, medicine may be a science, not an art." It's a fact, or it may take more time, but eventually the computer will explain the biodiversity between humans better than the doctor. However, precise algorithms are not a substitute for good doctors. They will still see the disease, not the people around them. As the mathematician Cathy O'Neil said in a TED talk: Don't treat algorithms as fair referees, they are not. The algorithm is just an idea embedded in the code. A truly personalized algorithm combines the patient's voice and defines the optimal solution based on what is most important to the patient, including pain relief, recovery, and life extension. What risks are they willing to take? What are their goals? " This will be a real revolution: from a biological point of view, it is precise and personal. What does this mean for our doctors? The road ahead is clear, and the era of slow and steady dependence on human clinical intuition is coming to an end, and the algorithm is used to predict treatment. The algorithm will become the touch of humanity, coupled with the empathy of patient preferences and needs, it will be the hallmark of great doctors of this era. (Source: Netease Technology) GMP Certificated Immune Globulin Injection Supplier in China Hepatitis B Immunoglobulin,Hep B Immunoglobulin,Hepatitis B Immunoglobulin Vaccine,Hepatitis Immune Globulin FOSHAN PHARMA CO., LTD. , https://www.foshanpharma.com