Watson and healthcare“I, for one, welcome our new computer overlords” – Ken Jennings, 7. Jeopardy! Champion. On Feb 1. 6 2. 01. IBM supercomputer, Watson, defeated two human all- time. Jeopardy! The. questions are often nuances with puns, irony, and humor. It is a. remarkable feat that a computer can even play this game, let alone beating. Is the age of artificial intelligence finally upon us. More specifically, can Watson's. As with Deep Blue before it, Watson started as a public. How can HR technology make a crucial difference in understanding your employee engagement survey results. The Results Summary of the Towers Watson solution shows each user a single. They can even search through.So, what. are those real world applications for Watson? It seems that Watson’s very first real world application is going to be in. Potentially, by answering questions for physicians at the. In this article, I will discuss how the Deep. QA technology behind. Watson can be used to solve specific problems in healthcare. All. information presented in this article is based on scientific papers. Watson research team and public interviews given by IBM. IBM is still formulating exactly how it will apply Deep. QA to. the medical domain. I would like to specifically thank Dr. Herbert Chase, a professor of. Clinical Medicine at Columbia University College of Physicians and. Surgeons, who is a key collaborator with IBM on Watson’s application in. A brief history of clinical decision support. For 4. 0 years, clinical decision support systems (CDSS) have promised to. In fact, when the government recently mandated. EHR) systems in all healthcare facilities, one. CDSS based on the patient data collected from the EHRs. With the large. amount of new data collected by the newly installed EHR systems, computers.
Watson will be able to find optimal answers to clinical questions. Two major categories of CDSS are diagnostic support tools and. Diagnostic support helps physicians. Diagnostic error is the number one cause of malpractice. Resources). Therefore, helping physicians avoid common cognitive. Treatment support, on the. The first generation of CDSS focuses on diagnostic support. Differential. diagnostic tools, like the DXPlain, use the Bayesian inference decision. The knowledge bases of such. Online Paid In Full The Story Of Harold Ryckman Missionary Pioneer To Paraguay A Nd Brazil Read Download PDF id. Charles Watson; George. Pioneer To Paraguay A Nd Brazil azw download DOWNLOAD Search Inside. The issue with these first generation tools is that. That is especially a problem now since. The second generation of clinical decision support tools aims to improve. A representative product in this category is. Isabel. Isabel has two major innovations. First, it takes a natural. EHR, identifies. keywords and findings contained in the summary, and then generates a list. Second, Isabel. indexes published medical literature for treatment options for each. The natural language process in both parsing the physician. Isabel. appealing. However, even with Isabel, it is still often too slow to extract physician. A study indicated that. Isabel's diagnoses are accurate when large paragraphs of text are used. Resources). For a trained medical professional, a better way to resolve a puzzling. Back to top. The power of simple Q& AAccording to an observational study published in 1. BMJ. (British Medical Journal) a team of researchers observed 1. Those physicians asked 1,1. The majority of those questions (6. Only two questions out of the 1,1. Enter Watson. People often ask, doesn't Google already do that? Sure, you can enter a. Google, and search for answers. In. fact, a doctor used Google as a diagnostic aid in high profile medical. New England Journal of Medicine (see Resources). However, Google is fundamentally a. It returns documents not answers. Google does not understand the question. The physician is responsible. Google results. Aside from the simplest factoid questions. In fact, there are whole books on. Google. Google finds millions of documents for each query, and orders the. The user needs to read the document and. Hence, while Google is tremendously useful, especially in answering factoid. CDSS tools that come before it. In a 2. 00. 6 study published by BMJ, two investigators went through a. New England Journal of. Medicine, and evaluated whether a trained professional can derive. Google search results. Note that the. human investigator must look at the cases to construct search queries and. Google results to identify potential diagnoses – a. The answer is that they can. Resources). The hope for Watson is that it would. For a good analysis of Google versus Watson in answering the type of. Jeopardy!, see Danny Sullivan's writing in the. Resources section. From the CDSS workflow point of view, we need to add a natural language and. Google, so that the computer. That is exactly what Watson does. Furthermore, Watson evaluates each potential answer based on evidence it. That allows Watson to give a. That is crucial for a medical Q& A. Premature closure happens when a. For example. when a patient walked into the office complaining of chest discomfort. But, when the patient later deteriorated and. This type of diagnostic error happens when the. In this case, a question. Q& A system asking why the heartburn medication did not work. Watson could do a great job in reminding physicians to. Back to top. The. Watson. From the technical point of view, Figure 1 shows the. Watson goes through to answer a question. In summary, the steps. Watson parses the natural language question to generate a search. Watson's embedded search engine searches a large document knowledge. Watson parses the natural language based search results and generates. Watson's embedded search engine searches supporting evidence. The search results are again parsed and each piece of. Each hypothesis is now assigned a score based on the strength. The hypotheses are turned into a list of answers returned to the. The key tasks performed by Watson include natural language processing. The workflow. Watson goes through to answer a question. Fundamentally, both the natural language parsing and evidence scoring are. Inside Watson. software components based on the Apache UIMA (Unstructured Information. Management Architecture) project perform those tasks. Watson generates. See Resources. Watson's way of reasoning is to generate hypotheses (that is, candidate. In fact, a major trend in scientific. While Watson is trying to. Watson too! See. the Resources section for an excellent article in. Wired magazine for more on this issue. Apache UIMAThe Apache UIMA project is an open source implementation of the OASIS UIMA. UIMA provides a scalable architecture framework to run text. Watson. A key feature of the UIMA framework is that it allows applications (called. UIMA terms) to be chained together. This way. each application component can focus on one text processing task, and pass. That is. ideally suited for the Watson workflow outlined earlier in the article. Furthermore, UIMA provides a parallel processing framework, called UIMA- AS. For. Java. In the case of. Watson, once a set of hypotheses is generated, the computer should be able. For example, all the parallel lines in Figure 1 represent tasks that can be processed concurrently by. CPUs. UIMA- AS is the reason Watson can leverage 2. CPUs to come. up with Jeopardy! This architecture. UIMA deployments to scale back when needed. For example, a. “physician assistant” application might not need to give answers within. Watson. From an application developer's point of view, writing a UIMA application. An annotator is a Java or C++. The UIMA documentation has an excellent tutorial on. Obviously, natural language processing requires more than just extracting. A large body of algorithms has. A key strength of the open source framework. UIMA is that it encourages other developers to contribute. Several commonly used annotators are already. UIMA distribution to help developers get started. The UIMA website hosts several large repositories of annotators. Open. NLP (Open Natural Language. Processing) annotators and IBM Semantic Search annotators. The IBM. Semantic Search annotators allow you to search a document repository for. Through the development of Watson, the IBM team developed many annotators. UIMA. In fact, a large amount of work went into developing scoring. According to the Watson team, more than. Jeopardy! Like Google, Watson's secret is not in how it finds the answers. Apache Lucene. As we described earlier, Watson searches large document databases to. One of the key search engines used to index and search those. Apache Lucene. Apache Lucene is a fully featured free text indexer and search engine. Java. It provides a set of simple APIs that allow developers to. The developer. can customize how the documents are indexed and scored for relevance. The UIMA annotators invoke Lucene as needed to search the. Lucene not only indexes free text in documents based on word frequency, it. UIMA. As UIMA processes natural language text in the document. CAS) objects, which. The Lucene CAS indexer (Lucas) is a standard annotator. UIMA. Lucas saves CAS information into Lucene index. UIMA and Lucene work together to form the analytics and knowledge engine. Watson. Even if Watson's annotators and algorithms are not open. Jeopardy! In 2. 00. Nature. published a special issue on how medical research is entering an area of. The scientific discovery process is shifting from theory. While the Nature issue focuses on genomic data as. For instance, as EHR systems are adopted by government mandate, physician. It is a large. repository of information to mine for symptom indicators, treatment. In fact, the Mayo Clinic and IBM. UIMA. annotators Mayo developed to mine its own medical records. Mining patient reported data is another interesting area. Patient. communities such as Patients. Like. Me and Association of Cancer Online. Resources, Inc. Important research has. FDA trials, as well as comparative studies on. Using natural language tools, we can take these. Using open source software and off- the- shelf hardware, Watson has shown us. The R& D effort around Watson has already started to. IBM contributions. UIMA, UIMA- AS, and related modules. It is now up to developers to write.
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