Abstract: A method and a system for efficient prediction of diseases is presented. Medical prediction systems usually learn and make predictions based on huge amount of raw clinical data, in the order of tens of thousands of data points which are sparse, episodic, and noisy. This approach requires big computing resources, which are unavailable to most health centres. In the disclosed approach, the dimensionality of the multitude raw data is automatically reduced by applying published disease protocol algorithm and guidelines to the huge number of patient features of raw data stored in EHR (Electronic Health Records), clinical text documents and clinical devices, to obtain few hundred data points which are fed to predicting machine both for the training phase and for the real time disease prediction. Thus, many health centres can benefit from the use of advanced prediction system to improve their performance, using their existing computer resources of.

Abstract: A method and a system for searching phrases in document sections is presented. Systems that sift through documents, such as medical documents, need to extract information from specific section of a document. The method is comprised of three phases, which are training phase, document preparation phase and search phase. During training phase, the section headers of documents are defined. Once training is completed, each document is preprocessed to generate search indexes, which also identifies the section in which a word of the document appears. In the search phase the user specifies, both the search phrase and the sections where the phrase has to be found.

Abstract: A system and method for fast concept search in multiple documents where the concept is expressed by plurality of words, all of which have to be in the same sentence and within specified range. The system automatically finds equivalent expressions of the same concept, and returns as search results all documents in which the concept is contained.

Abstract: System and method used to provide fast and accurate retrieval of findings results from large amounts of report documents (the corpus), such as medical record documents. The system maintains a dynamic list of the characteristics of no-finding called no-finding descriptors, each identified by a tag. Upon entering the corpus, the sentences of each new document are searched, and each sentence the content of which is similar to one of the descriptors is tagged. When search is conducted, the user enters a word or phrase, which expresses the subject of search. This subject is searched for in the corpus and from which a list of all sentences that contain the subject—the initial result list. This initial results list includes both finding and no-finding results. The final result list is obtained by extracting from the initial result list all occurrences of the tagged no-finding sentences.

Abstract: The invention relates to a method used by computers for searching words in documents written in a source language, which are not in the vocabulary of said source language, but are transcript of meaningful words in an origin language. The method is comprised of a preparation process and a search process. During the preparation process a database of unrecognized words in the source language is maintained, which contains, among other data, normalized phonetic conversion of the unrecognized word, as well as a corpus of all words of the documents in the search domain and indexes for efficient search. During search, a phonetic conversion and normalization is done for the search word, and the distance to similar phonetics words in the corpus is calculated. The found words in the corpus are arranged in ascending order, and the relevant documents are displayed.

Abstract: System and method used to provide fast and accurate retrieval of findings results from large amounts or report documents (the corpus), such as medical record documents. The system maintains a dynamic list of the characteristics of no-finding called no-finding descriptors, each identified by a tag. Upon entering the corupus, the sentences of each new document are searched, and each sentence the content of which is similar to one of the descriptors is tagged. When search is conducted, the user enters a word or phrase, which expresses the subject of search. This subject is searched for in the corpus and from which a list of all sentences that contain the subject—the initial result list. The initial results list includes both finding and no-finding results. The final result list is obtained by extracting from the initial result list all occurences of the tagged no-finding sentences.

Abstract: A system and method for fast concept search in multiple documents where the concept is expressed by plurality of words, all of which have to be in the same sentence and within specified range. The system automatically finds equivalent expressions of the same concept, and returns as search results all documents in which the concept is contained.

Abstract: The invention relates to a method used by computers for searching words in documents written in a source language, which are not in the vocabulary of said source language, but are transcript of meaningful words in an origin language. The method is comprised of a preparation process and a search process. During the preparation process a database of unrecognized words in the source language is maintained, which contains, among other data, normalized phonetic conversion of the unrecognized word, as well as a corpus of all words of the documents in the search domain and indexes for efficient search. During search, a phonetic conversion and normalization is done for the search word, and the distance to similar phonetics words in the corpus is calculated.