Release date: 2015-01-13
Who is Watson?
Watson is an artificial intelligence system developed by the DeepQA project team led by IBM's chief researcher David Ferrucci since 2007. It is the brainchild of more than 20 IBM researchers and is the founder of IBM Thomas J. • Name Watson's last name. Because of the efforts of scientists, Watson has the ability to understand natural language and answer questions accurately.
In 2011, Watson defeated the top prize winner Brad Ruttle and the winning streak holder Ken Jennings in a veteran variety show "Crisis Edge" in the United States, and has since entered the field of vision.
According to IBM's data, Watson's hardware is a cluster of 90 IBM Power 750 servers, which has a total of 2,880 Power7 processors and 16TB of memory. On the software side, Watson is written in Java and C++ and uses the Apache Hadoop framework for distributed computing, as well as the Apache UIMA (Unstructured Information Management Architecture) framework, IBM DeepQA software, and the SUSE Linux Enterprise Server 11 operating system.
Why is Watson so smart?
Watson can beat humanity in the game, how is it so smart? Watson stores millions of documents, including dictionaries, encyclopedias, news, literature, and other reference materials that build knowledge bases. Watson's hardware configuration allows it to process 500GB of data per second, which is equivalent to reading 1 million books per second.
According to Dr. Zhang Lei of IBM China Research Institute, after getting a question, Watson will conduct a series of calculations, including grammatical semantic analysis, searching each knowledge base, extracting alternative answers, and evidence of alternative answers. Search, calculation and synthesis of evidence strength, etc. Watson's main technical principle is to comprehensively judge and learn various possible answers by searching a lot of knowledge sources and using many small algorithms from multiple angles. One of the key steps is to evaluate the reliability of the alternative answers and to evaluate and quantify the reliability of the answers from multiple dimensions such as keywords, geographic locations, and types.
The history of robot doctor Watson?
In 2011, IBM said that because Watson can understand human language, it can ask for information from various sources by asking patients about their symptoms, medical history, using artificial intelligence techniques, natural language processing and analysis techniques. And data, prompt diagnosis and treatment advice. Since then, the Associated Press reporter personally experienced how the robot doctor Watson diagnosed the patient. The R&D staff provided a case of a virtual eye disease to "Watson" one by one, with blurred vision, family history of arthritis, and living in Connecticut. Pregnant with ... "Watson" proposed different diagnostic results, including uveitis, Behcet's disease, Lyme arthritis and so on. According to estimates, Watson's diagnostic accuracy rate reached 73%.
In 2011, American health care provider Wellpoint signed an agreement with IBM, which was Watson's first job. Watson’s main task is to help wellpoint nurses in complex cases complete their work while reviewing medical providers’ medical requests. And the application of late stage in clinical trials of tumors. Wellpoint's president also mentioned that in the future, Watson may also be able to obtain patient medical records and other information, and then comprehensive feedback to the doctor to improve the doctor's diagnosis speed.
In 2014, the University of Texas Anderson Cancer Center partnered with IBM to create the “moon landing projectâ€, which uses IBM Watson technology to eliminate cancer. The Anderson Cancer Center is the number one and the best-recognized best oncology hospital in the United States. The Center's Oncology Expert Advisor is driven by the Watson Cognitive Computing System to integrate clinicians and physicians at the Anderson Cancer Center. Researcher's knowledge. This OEA system will help clinicians develop, observe, and adjust treatment options for cancer patients. IBM Watson technology will also simplify and standardize the collection and integration of patient medical records, laboratory data and research data, enabling the collection of data to be integrated into the patient database of the Anderson Cancer Center, and then linking can be performed by advanced analysis techniques. In-depth analysis.
In addition to the Anderson Cancer Center, the Mayo Clinic is also conducting a concept test with IBM Watson to provide patients with appropriate clinical trials more quickly and efficiently. At any given time, the Mayo Clinic is able to conduct more than 8,000 human studies. But because there are not enough people to sign up, many clinical trials can't be done, whether it's at the Mayo Clinic or elsewhere. IBM and the Mayo Clinic are expanding Watson's knowledge corpus into public databases such as the Mayo Clinic and ClinicalTrials.gov, while training the knowledge base to analyze patient records and clinical trial conditions to provide the right match.
Thailand's Kangmin International Hospital uses IBM Watson Cognitive Computing to improve the quality of cancer treatment at the Bangkok Research Center and conduct case assessments in institutions in 16 countries. The hospital is committed to using Watson for Oncology technology developed in collaboration with the Kettering Cancer Center (MSK) over the next five years. The system will help doctors use medical evidence, academic research, MSK's extensive clinical technology, and each patient's record to develop effective treatment options for cancer patients.
In addition, the Sloan-Kettering Hospital in New York and the Cleveland Clinic have business cooperation with Watson.
On the enterprise side, Johnson & Johnson uses IBM Watson to read and understand research papers detailing the results of clinical trials, using the results to develop and evaluate medication options and other treatments. With this knowledge, Watson Discovery Advisor can help scientists identify any bad genetic files for drug samples. Before the comparative study, it took three people to spend an average of 10 months to collect the preparation data before they could start the analysis. The Johnson & Johnson team hopes to quickly integrate useful information directly from the medical literature through Watson, and can begin to directly ask questions about the data.
The development of artificial intelligence in the medical industry
In fact, as early as Watson, the relevant medical institutions were developing related "computer doctors" projects.
In the 1970s, researchers at the University of Pittsburgh developed the “Quick Medical Reference†software for the diagnosis of complex diseases in Punco. This medical diagnostic expert system collected 4,300 clinical characterizations that can diagnose more than 600 diseases. Program calculations to increase the likelihood of rapid diagnosis.
In 1972, Stanford University began to develop the MYCIN system, which was basically completed and put into use in 74 years. MYCIN is the suffix of many antibiotic names, so this is an expert system that helps doctors diagnose hospitalized blood-stained patients and treats them with antibiotics. It is still quite representative.
In the 1980s, the Massachusetts General Hospital began to develop and improve the DxPlan project. The areas of knowledge covered by DxPlan include most of the diseases and clinical characterization of the specialists in internal medicine, mainly using IBM's personal computer as a program development tool. Users can ask the computer what kind of inspection and testing should be done next, and get the most information with the least cost.
In the fall of 2010, the Isabel Health System was networked at the Orlando Health Hospital in Florida, USA, to provide doctors with reliable diagnosis and treatment recommendations. Some doctors with less experience and less clinical practice can get more help from the system. However, Isabel can only be used by networking with the multi-purpose hospital health system, which is slower and more expensive.
By 2013, computer doctor Watson was on the medical stage. He was both a cancer diagnostic expert and a professional in the management of medical service utilization. Since then, computer-aided diagnosis has opened a new page and officially entered the "Watson era."
According to market research firm Insight Research, the US healthcare industry will invest $69 billion in the information industry over the next six years. It is reported that Intel and SAP have begun to work with researchers at the University of California at Berkeley to develop competitive medical supercomputers.
Is the computer doctor really reliable?
As a computer doctor, Watson has the inherent advantages - its knowledge is much more than humans and will never be forgotten, the diagnostic accuracy is high, and you can always go to the clinic without rest, although this seems very exciting, but it can not help but appear A variety of questioning voices. The New York Times writer and Stanford doctor Abraham-Vieger said: "Watson may be a smart partner around us, but what I hear from patients and relatives and friends is not the lack of technology, but the opposite is the proliferation of technology." Watson Cohen of the Watson project team believes that Watson is only an aid. If doctors don't want to change, Watson can't change the medical industry. He said: "Some technologies do change the medical treatment. They provide treatments that were not available before, but IT is not like this. I think IT is just a promoter." Klaus-Peter Adrasen is a computer at the Vienna Medical University. The scientist is also the editor-in-chief of the Journal of Artificial Intelligence Medicine. In his opinion, a computer doctor like Watson, in essence, is actually a search engine that can answer various questions raised in natural language. Over time, computers will summarize their mistakes, but the knowledge they get from medical literature and case studies is very broad, and for medical staff, this knowledge is not necessarily very valuable in a clinical setting.
Practice is far from being as simple as processing data. The emotional comfort of patients and their families, grasping nuances in practice, and learning to grasp uncertainty, no matter what, is inseparable from human doctors. The most extensive medical data and top-notch processing power can't teach a computer how to care for a patient like a human doctor.
Watson is not a panacea. Although he is now famous, it is only a doctor assistant. The computer doctor's vision still needs a long way. Perhaps in the future, human-machine collaboration is the ultimate direction of development.
Source: Egg Yolk Technology
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