An assistive lower limb exoskeleton for people with neurological gait disorders.

Lower limb exoskeletons have already proven the capability to give back mobility to people suffering from spinal cord injury (SCI). Other important populations such as people with multiple sclerosis or muscular dystrophy, frail elderly and stroke victims, suffer from severe gait impairments and could benefit from similar technology. The work presented in the current paper describes a novel design of a 6-actuated degrees of freedom (DOFs) assistive lower limb exoskeleton for people with moderate mobility impairments. The electrical actuators are all remotely located on the back of the user for a more compact design with high dynamics. Cable driven solutions are used to transmit the flexion/extension of the hip and knee joints, while a powerful ballscrew carries out the hip adduction/abduction. The design of this exoskeleton, named AUTONOMYO, follows the key specifications of being highly back-drivable and able to perform dynamic motions at low energy consumption. AUTONOMYO is capable to assist the user's balance by providing complementary torques at the hip and the knee. Results show that the projected level of assistance for sit-to-stand transition varies from 50% to 100% in function of the user's bodyweight and height while higher level of assistance are reached for walking and stairs climbing activities.

Interchanging lexical information for a multilingual dictionary.

OBJECTIVE: To facilitate the interchange of lexical information for multiple languages in the medical domain. To pave the way for the emergence of a generally available truly multilingual electronic dictionary in the medical domain. METHODS: An interchange format has to be neutral relative to the target languages. It has to be consistent with current needs of lexicon authors, present and future. An active interaction between six potential authors aimed to determine a common denominator striking the right balance between richness of content and ease of use for lexicon providers. RESULTS: A simple list of relevant attributes has been established and published. The format has the potential for collecting relevant parts of a future multilingual dictionary. An XML version is available. CONCLUSION: This effort makes feasible the exchange of lexical information between research groups. Interchange files are made available in a public repository. This procedure opens the door to a true multilingual dictionary, in the awareness that the exchange of lexical information is (only) a necessary first step, before structuring the corresponding entries in different languages.

Synergy between medical informatics and bioinformatics: facilitating genomic medicine for future health care.

In this paper, we review the results of BIOINFOMED, a study funded by the European Commission (EC) with the purpose to analyse the different issues and challenges in the area where Medical Informatics and Bioinformatics meet. Traditionally, Medical Informatics has been focused on the intersection between computer science and clinical medicine, whereas Bioinformatics have been predominantly centered on the intersection between computer science and biological research. Although researchers from both areas have occasionally collaborated, their training, objectives and interests have been quite different. The results of the Human Genome and related projects have attracted the interest of many professionals, and introduced new challenges that will transform biomedical research and health care. A characteristic of the 'post genomic' era will be to correlate essential genotypic information with expressed phenotypic information. In this context, Biomedical Informatics (BMI) has emerged to describe the technology that brings both disciplines (BI and MI) together to support genomic medicine. In recognition of the dynamic nature of BMI, institutions such as the EC have launched several initiatives in support of a research agenda, including the BIOINFOMED study.

VUMeF: extending the French involvement in the UMLS Metathesaurus.

A considerable number of robust vocabularies and thesauri have been developed for the healthcare and biomedical domain. No single vocabulary, however; provides complete coverage of the information needs from a public health perspective. The results of an investigation of vocabulary sources for the development of a comprehensive controlled vocabulary for the public health domain at the Centers for Disease Control and Prevention (CDC) is presented.

Controlling the vocabulary for anatomy.

When confronted with the representation of human anatomy, natural language processing (NLP) system designers are facing an unsolved and frequent problem: the lack of a suitable global reference. The available sources in electronic format are numerous, but none fits adequately all the constraints and needs of language analysis. These sources are usually incomplete, difficult to use or tailored to specific needs. The anatomist's or ontologist's view does not necessarily match that of the linguist. The purpose of this paper is to review most recognized sources of knowledge in anatomy usable for linguistic analysis. Their potential and limits are emphasized according to this point of view. Focus is given on the role of the consensus work of the International Federation of Associations of Anatomists (IFAA) giving the Terminologia Anatomica.

Evaluating and reducing the effect of data corruption when applying bag of words approaches to medical records.

Unlike journal corpora, which are supposed to be carefully reviewed before being published, the quality of documents in a patient record are often corrupted by mispelled words and conventional graphies or abbreviations. After a survey of the domain, the paper focuses on evaluating the effect of such corruption on an information retrieval (IR) engine. The IR system uses a classical bag of words approach, with stems as representation items and term frequency-inverse document frequency (tf-idf) as weighting schema; we pay special attention to the normalization factor. First results shows that even low corruption levels (3%) do affect retrieval effectiveness (4-7%), whereas higher corruption levels can affect retrieval effectiveness by 25%. Then, we show that the use of an improved automatic spelling correction system, applied on the corrupted collection, can almost restore the retrieval effectiveness of the engine.

A humanist's legacy in medical informatics: visions and accomplishments of Professor Jean-Raoul Scherrer.

OBJECTIVE: To report about the work of Prof. Jean-Raoul Scherrer, and show how his humanist vision, his medical skills and his scientific background have enabled and shaped the development of medical informatics over the last 30 years. RESULTS: Starting with the mainframe-based patient-centered hospital information system DIOGENE in the 70s, Prof. Scherrer developed, implemented and evolved innovative concepts of man-machine interfaces, distributed and federated environments, leading the way with information systems that obstinately focused on the support of care providers and patients. Through a rigorous design of terminologies and ontologies, the DIOGENE data would then serve as a basis for the development of clinical research, data mining, and lead to innovative natural language processing techniques. In parallel, Prof. Scherrer supported the development of medical image management, ranging from a distributed picture archiving and communication systems (PACS) to molecular imaging of protein electrophoreses. Recognizing the need for improving the quality and trustworthiness of medical information on the Web, Prof. Scherrer created the Health-On-the-Net (HON) foundation. CONCLUSIONS: These achievements, made possible thanks to his visionary mind, deep humanism, creativity, generosity and determination, have made of Prof. Scherrer a true pioneer and leader of the human-centered, patient-oriented application of information technology for improving healthcare.

Conceptual search in electronic patient record.

Search by content in a large corpus of free texts in the medical domain is, today, only partially solved. The so-called GREP approach (Get Regular Expression and Print), based on highly efficient string matching techniques, is subject to inherent limitations, especially its inability to recognize domain specific knowledge. Such methods oblige the user to formulate his or her query in a logical Boolean style; if this constraint is not fulfilled, the results are poor. The authors present an enhancement to string matching search by the addition of a light conceptual model behind the word lexicon. The new system accepts any sentence as a query and radically improves the quality of results. Efficiency regarding execution time is obtained at the expense of implementing advanced indexing algorithms in a pre-processing phase. The method is described and commented and a brief account of the results illustrates this paper.

Comparing general and medical texts for information retrieval based on natural language processing: an inquiry into lexical disambiguation.

In this paper we compare two types of corpus, focusing on the lexical ambiguity of each of them. The first corpus consists mainly of general newspaper articles and literature excerpts, while the second belongs to the medical domain. To conduct the study, we have used two different disambiguation tools. First, each tool was validated in its respective application area. We then use these systems in order to assess and compare both the general ambiguity rate and the particularities of each domain. Quantitative results show that medical documents are lexically less ambiguous than unrestricted documents. Our conclusions emphasize the importance of the application area in the design of NLP tools.

Paragraph-oriented structure for narratives in medical documentation.

The authors present a 6 years experiment using a document- centered electronic patient record, based on a central document repository. The document management system is paragraph oriented and all documents are built automatically before editing using predefined ordered sets of para-graphs. Paragraphs can be preloaded with templates, text or images. Once edited, signed and printed, documents are again decomposed in paragraphs and permanently stored. This system, though the compositional aspect of paragraphs is limited and their semantic content wide, offers numerous advantages. The typology is easy to build and to maintain, it has been implemented widely in our hospitals without need for any natural language processing techniques and is used daily within commercially available text editors. The actual state of the system is discussed, emphasizing the structure of the documents, the various attributes and properties that have been needed in order to meet user's needs.

Evaluation of a command-line parser-based order entry pathway for the Department of Veterans Affairs electronic patient record.

OBJECTIVE: To improve and simplify electronic order entry in an existing electronic patient record, the authors developed an alternative system for entering orders, which is based on a command- interface using robust and simple natural-language techniques. DESIGN: The authors conducted a randomized evaluation of the new entry pathway, measuring time to complete a standard set of orders, and users' satisfaction measured by questionnaire. A group of 16 physician volunteers from the staff of the Department of Veterans Affairs Puget Sound Health Care System-Seattle Division participated in the evaluation. RESULTS: Thirteen of the 16 physicians (81%) were able to enter medical orders more quickly using the natural-language-based entry system than the standard graphical user interface that uses menus and dialogs (mean time spared, 16.06 +/- 4.52 minutes; P=0.029). Compared with the graphical user interface, the command--based pathway was perceived as easier to learn (P<0.01), was considered easier to use and faster (P<0.01), and was rated better overall (P<0.05). CONCLUSION: Physicians found the command- interface easier to learn and faster to use than the usual menu-driven system. The major advantage of the system is that it combines an intuitive graphical user interface with the power and speed of a natural-language analyzer.

A light knowledge model for linguistic applications.

Content extraction from medical texts is achievable today by linguistic applications, in so far as sufficient domain knowledge is available. Such knowledge represents a model of the domain and is hard to collect with sufficient depth and good coverage, despite numerous attempts. To leverage this task is a priority in order to benefit from the awaited linguistic tools. The light model is designed with this goal in mind. Syntactic and lexical information are generally available with large lexicons. A domain model should add the necessary semantic information. The authors have designed a light knowledge model for the collection of semantic information on the basis of the recognized syntactical and lexical attributes. It has been tailored for the acquisition of enough semantic information in order to retrieve terms of a controlled vocabulary from free texts, as for example, to retrieve Mesh terms from patient records.

Looking back or looking all around: comparing two spell checking strategies for documents edition in an electronic patient record.

We report on the comparison of two systems for correcting spelling errors resulting in non-existent words (i.e. not listed in any lexicon). Both systems aim at improving edition of medical reports. Unlike traditional systems, based on word language models, both semantic and syntactic contexts are considered here. Both systems share the same string-to-string edit distance module, and the same contextual disambiguation principles. The differences between the two systems are located at the user interaction level: while the first system is using exclusively the left context, simulating the underlining of every mis-spelling at the end of every word typing, the second system uses the left as well as the right context and simulate a post-edition correction, when asked by the author. Our conclusion shows the improvements brought by the second approach.

Semantic handling of medical compound words through sound analysis and generation processes.

Compound words are frequently encountered in the medical domain. Their conciseness complies with the telegraphic style usually adopted by clinicians in daily practice. This amplifies the need for clarifying their semantic interpretation and representation through respectively the analysis and generation processes. While highlighting the peculiarities of medical compound words, this paper shows how model-driven linguistic tools accurately deal with the compositionality of medical language. These statements are illustrated by means of examples, stemming from the handling of surgical procedures as part of the GALEN-IN-USE project.

Medical document anonymization with a semantic lexicon.

We present an original system for locating and removing personally-identifying information in patient records. In this experiment, anonymization is seen as a particular case of knowledge extraction. We use natural language processing tools provided by the MEDTAG framework: a semantic lexicon specialized in medicine, and a toolkit for word-sense and morpho-syntactic tagging. The system finds 98-99% of all personally-identifying information.

GALEN: a third generation terminology tool to support a multipurpose national coding system for surgical procedures.

Generalised architecture for languages, encyclopedia and nomenclatures in medicine (GALEN) has developed a new generation of terminology tools based on a language independent model describing the semantics and allowing computer processing and multiple reuses as well as natural language understanding systems applications to facilitate the sharing and maintaining of consistent medical knowledge. During the European Union 4 Th. framework program project GALEN-IN-USE and later on within two contracts with the national health authorities we applied the modelling and the tools to the development of a new multipurpose coding system for surgical procedures named CCAM in a minority language country, France. On one hand, we contributed to a language independent knowledge repository and multilingual semantic dictionaries for multicultural Europe. On the other hand, we support the traditional process for creating a new coding system in medicine which is very much labour consuming by artificial intelligence tools using a medically oriented recursive ontology and natural language processing. We used an integrated software named CLAW (for classification workbench) to process French professional medical language rubrics produced by the national colleges of surgeons domain experts into intermediate dissections and to the Grail reference ontology model representation. From this language independent concept model representation, on one hand, we generate with the LNAT natural language generator controlled French natural language to support the finalization of the linguistic labels (first generation) in relation with the meanings of the conceptual system structure. On the other hand, the Claw classification manager proves to be very powerful to retrieve the initial domain experts rubrics list with different categories of concepts (second generation) within a semantic structured representation (third generation) bridge to the electronic patient record detailed terminology.

Power of expression in the electronic patient record: structured data or narrative text?

This paper presents the authors' experience with the development and use of a document-centered electronic patient record (EPR) in a large teaching hospital. The development of the document-centered EPR began with the formulation of a set of critical hypotheses to facilitate both the continuation of the best medical practice and the implementation and use of the EPR. An alternate and more conventional approach - the data-centered EPR - is compared with the document-centered EPR. Various benefits and pitfalls are discussed. Finally, the choice was to offer both solutions in a tightly linked system. The need for an EPR which combines the document and data centered approaches is a reflection of the more general discussion of what the medical record will be in the future. All too often, the need for structured data conflicts with the need for free texts and the power of expression. It is not easy to evaluate the consequences of this initial decision. However, changing the foundations of the EPR after its implementation is difficult and expensive. Therefore, the selection of the correct orientation in a given hospital requires a broad-based discussion.

Fast exact string pattern-matching algorithms adapted to the characteristics of the medical language.

OBJECTIVE: The authors consider the problem of exact string pattern matching using algorithms that do not require any preprocessing. To choose the most appropriate algorithm, distinctive features of the medical language must be taken into account. The characteristics of medical language are emphasized in this regard, the best algorithm of those reviewed is proposed, and detailed evaluations of time complexity for processing medical texts are provided. DESIGN: The authors first illustrate and discuss the techniques of various string pattern-matching algorithms. Next, the source code and the behavior of representative exact string pattern-matching algorithms are presented in a comprehensive manner to promote their implementation. Detailed explanations of the use of various techniques to improve performance are given. MEASUREMENTS: Real-time measures of time complexity with English medical texts are presented. They lead to results distinct from those found in the computer science literature, which are typically computed with normally distributed texts. RESULTS: The Boyer-Moore-Horspool algorithm achieves the best overall results when used with medical texts. This algorithm usually performs at least twice as fast as the other algorithms tested. CONCLUSION: The time performance of exact string pattern matching can be greatly improved if an efficient algorithm is used. Considering the growing amount of text handled in the electronic patient record, it is worth implementing this efficient algorithm.

Tagging medical texts: a rule-based experiment.

In this paper we describe the construction of a part-of-speech tagger for medical document retrieval purposes, therefore we have designed a specific architecture called minimal commitment. The system uses local grammatical rules for conducting the disambiguation task. Four evaluations are conducted, with and without taking unknown words into account. In between each evaluation the modules (lexicon, guesser, rules) of the system are incrementally improved.