If the topic is hot, artificial intelligence is undoubtedly one of the hottest topics in the near future. Microsoft, Google, Facebook, IBM and other technology giants are competing to deploy artificial intelligence. In addition to the superficial marketing gimmick, it is also regarded as its business competitiveness. And the need for transformation, and the value of artificial intelligence in the medical field, the industry has different opinions, then, is artificial intelligence "inserted" in the medical field is a chicken rib or positive energy?
What are the benefits of artificial intelligence combined with medical imaging?
In recent years, with the rapid development of emerging technologies such as mobile internet and Internet of Things, the amount of data generated by different terminal devices has become increasingly large. According to relevant agencies, the amount of big data will rise to 44ZB in 2020. It is understood that up to 80% of these data are derived from unstructured data such as text, images, and video. However, due to technical bottlenecks, existing IT systems cannot recognize these unstructured data. Therefore, the data is like "junk." ", become worthless. The cognitive technology of artificial intelligence is an inevitable product of the era of big data. It can not only identify a large amount of unstructured data, but also provide data insight. (Cognitive computing is a concept proposed by IBM. From a technical point of view, Cognitive computing and artificial intelligence have many commonalities, such as machine learning and deep learning. However, artificial intelligence is only one dimension of cognitive computing. Artificial intelligence emphasizes making machines more human, while cognitive computing is more Emphasis on reasoning and learning, and how to combine such capabilities with specific business applications and solve business problems). IBM's Greater China Hardware System Server Solution Shi Dongfeng once said that cognitive computing is a kind of world that can think and perceive the world like human beings. It has three prominent characteristics of understanding, reasoning and learning, and can understand various forms of non-structure. Data is generated to generate insights that enable companies to quickly gain insights from complex, massive amounts of data and make more informed business decisions.
In fact, some high-tech companies at home and abroad have applied advanced technologies such as cognitive computing and deep learning to the field of medical imaging, and there have been “robot doctorsâ€, and IBM’s “Doctor Watson†is the most representative. In the context of domestic medical informationization and grading diagnosis and treatment, the market space for artificial intelligence and medical imaging is growing.
For doctors, the memory capacity and time of the brain are limited. It is impossible for most doctors to read and understand the latest tens of thousands of research papers, and it is even more impossible to remember the tens of thousands of diseases that humans may suffer. . But for artificial intelligence, "robot doctors" can use continuous learning techniques to continuously access a large number of medical reference books, medical journals, clinical diagnostic manuals, medical electronic records, to encyclopedias, dictionaries, books, news, and even screenplays. The electronic medical records mentioned are machine learning, and almost all the latest medical knowledge can be stored in time. And more importantly, robotic doctors can apply what they have learned, using cognitive analysis techniques, and relying on massive amounts of data collected from various sources to quickly give “opinions†to guide doctors in making diagnosis and treatment decisions, and not because People's emotions lead to lack of diagnosis or misdiagnosis, while patients can get medical services more quickly, and medical institutions can also save costs.
Previously, cognitive analysis of more than 90% of unstructured medical image data has been a blank because of the high technical barriers associated with big data medical image analysis technology and computer cognitive computing technology, and cognitive technology is just making up for it. This technology gap, the commercial value of artificial intelligence in the field of medical imaging can not be ignored. According to information provided by IBM, as early as 2014, IBM's "Watson Doctor" has been employed at the MD Anderson Cancer Center, and has been hailed as "the best cancer expert of the future" and "medical". God." According to estimates, Watson's diagnostic accuracy rate reached 73%.
Artificial intelligence combined with medical imaging has many benefits, benefiting patients, physicians and medical care. For patients, it is possible to complete health check more quickly, obtain more accurate diagnosis suggestions and personalized treatment plan suggestions; for doctors, it can reduce the time of reading, assist diagnosis, reduce the probability of misdiagnosis and suggest possible side effects. For medical treatment, deep learning can improve the preparation rate and reduce the medical cost systematically.
Sprinkler irrigation and micro-irrigation automatic control equipment With the development of economy, water resources, energy shortage and labor cost increase, more and more water-saving irrigation systems will adopt automatic control. This article focuses on the advantages and classification of automated irrigation.
The advantages are as follows:
(1) It is possible to truly control the amount of irrigation, irrigation time and irrigation cycle in a timely and appropriate manner, thereby increasing crop yield and significantly improving water utilization.
(2) Saving labor and operating expenses.
(3) The work plan can be arranged conveniently and flexibly, and the management personnel do not have to go to the field at night or other inconvenient time.
(4) Since it can increase the effective working time every day, the initial capital investment in pipelines, pumping stations, etc. can be reduced accordingly.
classification:
First, fully automated irrigation system
The fully automated irrigation system does not require direct human involvement. The pre-programmed control procedures and certain parameters that reflect the water requirements of the crop can automatically open and close the pump for a long time and automatically irrigate in a certain order. The role of the person is simply to adjust the control program and overhaul the control equipment. In this system, in addition to emitters (heads, drip heads, etc.), pipes, fittings, pumps, and motors, it also includes central controllers, automatic valves, sensors (soil moisture sensors, temperature sensors, pressure sensors, water level sensors, and rain sensors). Etc.) and wires.
Second, semi-automatic irrigation system
In the semi-automated irrigation system, no sensors are installed in the field. The irrigation time, irrigation volume and irrigation period are controlled according to pre-programmed procedures, rather than feedback based on crop and soil moisture and meteorological conditions. The degree of automation of such systems is very different. For example, some pump stations implement automatic control, and some pump stations use manual control. Some central controllers are only one timer with simple programming function, and some systems have no central control. The controller, but only some of the sequential switching valves or volume valves are installed on each branch pipe.
Automated irrigation is the trend of the times. In the future water-saving irrigation projects, more and more automated irrigation systems will be applied.
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