Case sharing: Connow--learning in large medical data

Connow is a start-up that is committed to starting a business in a large medical data field. By providing users with http://www.aliyun.com/zixun/aggregation/12034.html "> wearable devices that continuously record the user's physical signs (such as blood pressure, heart rate, blood sugar, etc.), and then send the data to the cloud, And then through the cloud algorithm for these data analysis, to obtain the user's own continuous signs fluctuation law, when the fluctuation occurs when there is an unexpected warning appears.

In May this year, Xiao Bian had the privilege of interviewing one of Connow's founders, but for a variety of reasons, the interview has not been published. Today, the record of the interview again, found that there are a lot of wonderful content, now sorted out, and share with you.

Connow Service mode vs Hospital Service Model

The Connow collection is a continuous physical sign data, and its every judgment is not based on the user's latest point of data, but based on previous data. Wearable equipment must be different from the analysis method of hospital service system. Hospital service system is, when you have a feeling of discomfort, before going to the hospital to do the inspection, the doctor with sophisticated medical equipment for you after the examination, the value of your judgment, to understand your body may be a health abnormality, and then give you the appropriate treatment plan. But this model exists the biggest problem is that the first person to take the initiative to the hospital, the hospital can not change in people's health at the beginning of the moment to intervene, so the hospital service model, medical model must be treatment, and can not do disease prevention, and wearable equipment, although the precision will never reach the level But its value is that it has a sufficient amount of data, not hospital single point data, but continuous data. This can be done to the "not ill" warning.

The big Data age is full of data, in fact, in the future, people will produce more and more data, every minute each person is producing different data, but not previously captured, now through wearable equipment can capture more data, at this time could not use the original sampling method for the corresponding analysis. The hospital is actually in the form of sampling analysis, it is necessary to maintain a precise state of measurement, so as to effectively reflect your physical condition, which is actually the concept of statistical data. The big data concept is to say, not to emphasize precision, but to emphasize the persistence of data, through the continuity of data to find the relationship between phenomena and phenomena.

When the wearable equipment collection of data breadth is large enough, we will no longer analyze the single point of exceeding the standard, we want to analyze the fluctuation of the physical signs is not the law, first of all to establish a normal human baseline law is what kind of, second, to solve the abnormal fluctuation of the health risks corresponding to what kind 2012 Connow obtained exclusive authorization from the University of Minnesota Time Biology Center in 20 and can use the center's baseline data and analysis model. This allows Connow to handle the continuous data submitted by a large number of people in parallel, and then analyze their data rather than checking it at a point like a hospital.

Importance of continuous signs data

Any healthy changes of all people, the central nervous Center will adjust the physical signs reflected, and signs of abnormalities, must be persistent abnormalities. Connow by capturing this persistent anomaly and making the corresponding output, the comparative discovery that the future risk of the user is expected to be there, is the basis of Connow's entire theory.

But each age phase of the normal physical signs data range values are different, to blood pressure, for example, the young people's range is low, and the elderly's range is high, so we should analyze the continuous data, dynamic to see, rather than look at the single point of data, do not do regular analysis. The problem with wearable devices is how to get more dense data in a good user experience, and its value depends on what kind of data density it can acquire, and the computational and analytical capabilities should not be on the device, but in the background cloud. As the data becomes more plentiful, the data algorithm will be more accurate, and there will be more comparative value. Users can land directly in the cloud, crawl data and analysis results, and then compare all the data horizontally and vertically.

Give another example of continuous sign data. All NASA astronauts are at the University of Minnesota Time Biology Center Laboratory helping them with physical signs. NASA raised a project early last year to understand the impact of dramatic changes in the environment on human signs. NASA has since 1960, the world's seven-magnitude earthquake in the region listed, to see if there was no laboratory testing personnel signs data changes, the results found that two are consistent, one is the 2008 Wenchuan earthquake, because in Chengdu, China has a laboratory to do biological research, There is a communication with the lab, and one is the 2011 Tokyo earthquake, there is a hospital in Tokyo and laboratory cooperation, so there is data exchange. Data recalls that three days before the quake, the test's blood pressure data has been abnormal, to the earthquake three days before the restoration of the original state. This means that any creature is actually capable of perceiving a dramatic change in the environment, lower-level organisms are obvious, as we all know, people actually have sensory ability, but people are senior creatures, eyes and ears to receive too much information, so can not perceive the body's blood pressure changes, but the central nervous is able to catch this abnormal change , and the secretion of hormones to regulate the changes in the body signs, this change although they do not feel, but data statistics can be found.

Connow Target Market

According to the Health ministry's report, China's current hypertension patients are 260 million, which means that in the 35-year-old population, every three people are hypertensive patients, and 70% people do not know that they are suffering from high blood pressure.

The target market for Connow is not the self-sufficient market for the elderly, but the market that children buy for their parents. According to the current data, most of the blood pressure meter is the children through the electrical business online to buy. Because children can not accompany parents, but also want to understand the health of parents, this is the Connow market demand. Parents use Connow products, children will receive SMS reminders, you can understand the health of parents information: First, a parent has not persisted in the test, because he only insists on testing, the more data, there can be analysis of the way; second monitored data that children can see today monitored several times; With the monitoring data can be integrated analysis and judgement, in this case, the parents of the health risk factor is not high, if the health risk coefficient is high, then this situation persists, will have what risk, thus take corresponding measures.

Connow's equipment collects data at a frequency of One days a week. Children only need to call their parents once a week, reflect the parents to charge equipment in advance, the next day to wear a day, the third day may see all the data analysis results, and then each month, will give a rough analysis of the report: first, the analysis of the health of parents, the second is the risk of several major malignant diseases have no, Third, compared with the level of the situation, so that children will be very clear about the health of the family is probably what kind of, need not to go to the hospital, need not change their lives.

Connow Profit model

Connow's profit model is similar to that of other wearable equipment manufacturers, that is, paid hardware plus one year free service, and the second year of the second year, users can choose to pay, or they can choose not to pay. Without payment, data is not networked, and is not available for service, data is not collected, but the basic function of the equipment is maintained, you can continue to use, if you pay, you can obtain data automatic acquisition and Analysis Services, the ownership of the data are still users, and blood pressure and other data is not as strong as the privacy of genetic data, So it doesn't involve too much intrusion into user privacy issues.

The question of pay depends largely on the wishes of the children. From the whole big market, first of all, from the structure, the two young people to support four elderly people are very much, young people must go to work and life, when the elderly body problems, family, work and life are all messed up. Too many children sell homes to treat the elderly, 85% of the Chinese people lifetime treatment costs, 70% for the last six months. Therefore, from this point of view, Connow market potential is still relatively large.

In the future, Connow's goal is to I hope that in the future everyone will wear a variety of sensors to monitor their own signs, before the formation of symptoms can be found abnormal signs, through the abnormal signs of timely warning and reminders, and to give some improvement of the program, so as not to go to the stage of illness.

(Responsible editor: The good of the Legacy)