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PubMed2005

[Elemental research on intelligent non-invasive temporary pacemakers].

Some research on intelligent non-invasive temporary pacemakers is introduced in this paper. An industrial computer, some IC chips and other elements are used to construct its hardware, and its software is in C++ language. The experimental device has some intelligent functions of recognizing some arrhythmia. The system has a pacemaker module and an ECG monitor module. Its software includes a main program, a RS-232C communication program, a printer VxD, a pacing control VxD and ECG signal pretreatment and recognizing program and so on. The pacing-generating circuit is employed to make the precision control of pacing current. The communication between industrial-computer system and ECG module is completed through the DLL. The real time processing of ECG signals is based on filter method for a higher recognizing ratio. The system calculates several parameters to recognize certain arrhythmia and uses MIT/BIH database to validate the reliability of ECG recognition.

Algorithms↗

PubMed1994

Intelligent systems in patient monitoring and therapy management. A survey of research projects.

Although today's advanced biomedical technology provides unsurpassed power in diagnosis, monitoring, and treatment, interpretation of vast streams of information generated by this technology often poses excessive demands on the cognitive skills of health-care personnel. In addition, storage, reduction, retrieval, processing, and presentation of information are significant challenges. These problems are most severe in critical care environments such as intensive care units (ICUs) and operating room (ORs) where many events are life-threatening and thus require immediate attention and the execution of definitive corrective actions. This article focuses on intelligent monitoring and control (IMC), or the use of artificial intelligence (AI) techniques to alleviate some of the common information management problems encountered in health-care environments. This article presents the findings of a survey of over 30 IMC projects. A major finding of the survey is that although significant advances have been made in introducing AI technology in critical care, successful examples of fielded systems are still few and far between. Widespread acceptance of these systems in critical care environments depends on a number of factors, including fruitful collaborations between clinicians and computer scientists, emphasis on evaluation studies, and easy access to clinical information.

Artifacts↗

PubMed1997

Case-based learning of plans and goal states in medical diagnosis.

We introduce a case-based system, BOLERO, that learns both plans and goal states. The major aim is that of improving the performance of a rule-based diagnosis system by adapting its behavior using the most recent information available about a patient. On the one hand BOLERO gets knowledge from cases in the form of diagnostic plans that are represented as sequences of decision steps. The advantages of this representation include: (1) retrieval and adaptation of parts of plans (steps) appropriate to the current problem state; (2) generation of new plans not previously available in memory; and (3) learning from experience, both from successful or failed plans. On the other hand, since goal states are sets of final diagnosis likelihoods they are not known beforehand, i.e. goal states are not defined and the system has to learn to recognize them. For this reason BOLERO has a case-based method that uses solutions of past cases to recognize a diagnostic state as a goal state of a new planning problem. BOLERO and a rule-based system are integrated into a meta-level architecture in which we emphasize the collaboration of both systems in solving problems. The rule-based system executes the plans generated by BOLERO. As a consequence of the execution of plans, the rule-based system furnishes BOLERO with new information with which BOLERO can generate a new plan to adapt the reasoning process of the rule-based system into correspondence with the recent available data. All the methods have been designed to be useful for medical diagnosis and have been tested in the domain of diagnosing pneumonia.

Artificial Intelligence↗

PubMed2026

Genomic profiling as an option for ovarian cancer diagnostics.

INTRODUCTION: Ovarian cancer (OC) is a highly heterogeneous and lethal gynecological malignancy. Precision oncology has shifted the management paradigm to comprehensive molecular profiling. Genomic-based diagnostics are now a clinical necessity for accurate prognostic stratification and the rational selection of targeted therapeutics, such as PARP and immune checkpoint inhibitors. AREAS COVERED: This review evaluates current literature regarding the distinct genomic landscapes defining OC histotypes to underlined the role of molecular profiling in the diagnostic field of OC. We discuss the practical implementation, technical aspect, and clinical validity of the main molecular diagnostic platforms, focusing on tissue-based Comprehensive Genomic Profiling (CGP) and Homologous Recombination Deficiency (HRD). Furthermore, we explore emerging translational data on liquid biopsy (LBx) applications. EXPERT OPINION: While current tissue-based methodologies provide critical baseline data, the OC diagnostic paradigm must pivot from static testing to proactive and longitudinal tracking. Integrating advanced LBx approaches enables a real-time monitoring of dynamic parameters as minimal residual disease (MRD) and acquired resistance. Integrating these dynamic blood-based assays with multi-omic profiling and artificial intelligence (AI)-driven tools allows a full understanding of the complex tumor behavior.

Humans↗

PubMed2004

Generating high-speed dynamic running gaits in a quadruped robot using an evolutionary search.

Over the past several decades, there has been a considerable interest in investigating high-speed dynamic gaits for legged robots. While much research has been published, both in the biomechanics and engineering fields regarding the analysis of these gaits, no single study has adequately characterized the dynamics of high-speed running as can be achieved in a realistic, yet simple, robotic system. The goal of this paper is to find the most energy-efficient, natural, and unconstrained gallop that can be achieved using a simulated quadrupedal robot with articulated legs, asymmetric mass distribution, and compliant legs. For comparison purposes, we also implement the bound and canter. The model used here is planar, although we will show that it captures much of the predominant dynamic characteristics observed in animals. While it is not our goal to prove anything about biological locomotion, the dynamic similarities between the gaits we produce and those found in animals does indicate a similar underlying dynamic mechanism. Thus, we will show that achieving natural, efficient high-speed locomotion is possible even with a fairly simple robotic system. To generate the high-speed gaits, we use an efficient evolutionary algorithm called set-based stochastic optimization. This algorithm finds open-loop control parameters to generate periodic trajectories for the body. Several alternative methods are tested to generate periodic trajectories for the legs. The combined solutions found by the evolutionary search and the periodic-leg methods, over a range of speeds up to 10.0 m/s, reveal "biological" characteristics that are emergent properties of the underlying gaits.

Algorithms↗

PubMed2004

A knowledge-based framework for image enhancement in aviation security.

The main aim of this paper is to present a knowledge-based framework for automatically selecting the best image enhancement algorithm from several available on a per image basis in the context of X-ray images of airport luggage. The approach detailed involves a system that learns to map image features that represent its viewability to one or more chosen enhancement algorithms. Viewability measures have been developed to provide an automatic check on the quality of the enhanced image, i.e., is it really enhanced? The choice is based on ground-truth information generated by human X-ray screening experts. Such a system, for a new image, predicts the best-suited enhancement algorithm. Our research details the various characteristics of the knowledge-based system and shows extensive results on real images.

Algorithms↗

PubMed2003

Data mining tools for biological sequences.

We describe a methodology, as well as some related data mining tools, for analyzing sequence data. The methodology comprises three steps: (a) generating candidate features from the sequences, (b) selecting relevant features from the candidates, and (c) integrating the selected features to build a system to recognize specific properties in sequence data. We also give relevant techniques for each of these three steps. For generating candidate features, we present various types of features based on the idea of k-grams. For selecting relevant features, we discuss signal-to-noise, t-statistics, and entropy measures, as well as a correlation-based feature selection method. For integrating selected features, we use machine learning methods, including C4.5, SVM, and Naive Bayes. We illustrate this methodology on the problem of recognizing translation initiation sites. We discuss how to generate and select features that are useful for understanding the distinction between ATG sites that are translation initiation sites and those that are not. We also discuss how to use such features to build reliable systems for recognizing translation initiation sites in DNA sequences.

Artificial Intelligence↗

PubMed1991

Edge extraction by active defocusing.

A novel edge extraction method that employs an active defocusing technique is presented. The method is based on the principle that a Laplacian-of-Gaussian (LOG) operation can be approximated by a Difference-of-Gaussian (DOG) operation. While such an operation is usually done in digital image processing, it can also be very effective conducted in a combination of optical techniques and digital processing. In this edge extraction method, a focused image of an object in a scene is first acquired. The image of the scene is then slightly defocused by changing the focal length of the camera. A real time subtraction operation is applied to subtract the defocused image from the previously acquired image. It produces a residual image that emphasizes abrupt intensity variations. An objective evaluation, called an edge index, is performed on the resulting image. The amount of defocusing is carefully adjusted according to this measurement so that a desired edge image is generated. Boundaries of objects can then be obtained by further enhancement of the edge image. Since this edge detection method is an optical-based process aided by digital processing, it is fast and relatively inexpensive.

Artificial Intelligence↗

PubMed1998

Automated clustering and assembly of large EST collections.

The availability of large EST (Expressed Sequence Tag) databases has led to a revolution in the way new genes are cloned. Difficulties arise, however, due to high error rates and redundancy of raw EST data. For these reasons, one of the first tasks performed by a scientist investigating any EST of interest is to gather contiguous ESTs and assemble them into a larger virtual cDNA. The REX (Recursive EST eXtender) algorithm described in this paper completely automates this process by finding ESTs that can be clustered on the basis of overlapping bases, and then assembling the contigs into a consensus sequence. By combining the clustering and assembly steps, REX can quickly generate assemblies from EST databases that are frequently updated without having to preprocess the data. A consensus assembly method is used to correct miscalled bases and remove indel errors. A unique feature of this method is that it addresses the issues of splice variants and unspliced cDNA data. Since REX is a fast greedy algorithm, it can address the problem of generating a database of assembled sequences from very large collections of EST data. A procedure is described for creating and maintaining an Assembled Consensus EST database (ACE) that is useful for characterizing the large body of data that exists in EST databases.

Algorithms↗

PubMed1990

Escherichia coli molecular genetic map (1000 kbp): update I.

The sequenced genes from Escherichia coli that are available in the EMBL library (release 21) have been localized on an updated and corrected version of the restriction map of the chromosome generated by Kohara et al. (1987). One thousand kbp of sequenced DNA are incorporated in this update; this is equivalent to 23% of the total genome. The accuracy of the map is assessed, and it is corrected and updated where appropriate. A significant number of sites were missing from the original map, mainly involving two of the eight enzymes used by Kohara et al. (1987), ie. PvuII and EcoRV. The nucleotide environment of such missing sites was examined and, using an Artificial Intelligence approach, it appears that the site for these enzymes is sensitive to context effects. Several genes of known position on the E. coli chromosome could not be placed on the restriction map; this suggests that additional gaps are likely to exist on the restriction map, in addition to the original seven identified by Kohara et al. We have also obtained information about the probable direction of transcription of chromosomal genes with respect to the map. Most genes are transcribed in the same direction as the replication forks, particularly around oriC at 84 min.

Artificial Intelligence↗

PubMed2000

An evaluation of an intelligent home monitoring system.

A trial was performed of an intelligent monitoring system which used sensors in the home to identify emergencies by detecting deviations from normal activity patterns. The field trial lasted three months. Twenty-two elderly people agreed to participate. Their ages ranged from early 60s to over 85, with two-thirds in the age range 75-84 years. They lived in four different localities within the UK--Ipswich, Northumberland, Merseyside and Nottingham. A total of 61 alerts was recorded, at a mean frequency about one alert per month per client. Of the 61 alerts generated, 46 were classified as false alerts and the other 15 as genuine, although no real emergencies occurred during the study. Many people in the field trial reported enhanced feelings of safety and security, which could help to stimulate independence and help them to remain living in their own homes. The monitoring system increased the care choices available to elderly people and supported and enhanced the carer's role.

Aged↗

PubMed1993

Intelligent Medical Record--entry (IMR-E).

This paper describes an automated medical record designed to allow providers to enter patient data at the point of care. The system runs on PCs and Macintoshes and uses a graphical user interface and object-oriented programming to take advantage of current mouse and pen technologies. The provider acquires all relevant patient data by pointing and clicking at selections on input screens, many of which contain anatomical drawings to help the provider quickly and accurately describe patient findings. The system also generates a grammatically correct progress note using the problem-oriented structure. Furthermore, items identified in the assessment and plans portion of the program can be ported to expert systems for medical decisions assistance or to billing systems. The system allows the provider to obtain the necessary information on a focused patient visit in less than 5 min or to enter a complete history and physical.

Artificial Intelligence↗

PubMed2000

The future of bedside monitoring.

Today's intensivists are provided with more information than ever before, yet current monitors present data from multiple sources in a relatively raw form with virtually no intelligent data integration and processing. In the next century, technological advances in miniaturization, biosensors and computer processing, coupled with an improved understanding of critical illnesses at the molecular level, will lead to the development of a new generation of monitors. Monitoring will move from the traditional macroscopic invasive approach to a noninvasive, molecular analysis of evolving critical disease processes. It is likely that disturbances in homeostasis will become known immediately or before they would otherwise be manifest clinically. Nanotechnology will permit monitoring of critical changes in the intracellular environment or the by-products of cellular metabolism and signal messaging. This article discusses monitoring technologies that hold promise for further development in the next century and point out techniques likely to be abandoned.

Artificial Intelligence↗

PubMed2001

Case-based reasoning for antibiotics therapy advice: an investigation of retrieval algorithms and prototypes.

We have developed an antibiotics therapy advice system called ICONS for patients in an intensive care unit (ICU) who have caught an infection as additional complication. Since advice for such critically ill patients is needed very quickly and as the actual pathogen still has to be identified by the laboratory, we use an expected pathogen spectrum based on medical background knowledge and known resistances. The expected pathogen spectra and the resistance information are periodically updated from laboratory results. To speed up the process of finding suitable therapy recommendations, we have applied case-based reasoning (CBR) techniques. As all required information should always be up to date in medical expert systems, new cases should be incrementally incorporated into the case base and outdated ones should be updated or erased. For reasons of space limitations and of retrieval time an indefinite growth of the case base should be avoided. To fulfill these requirements we propose that specific single cases should be generalised to more general prototypical ones and that subsequent redundant cases should be erased. In this paper, we present evaluation results of different generation strategies for generalised cases (prototypes). Additionally, we compare measured retrieval times for two indexing retrieval algorithms: simple indexing, which is appropriate for small and medium case bases, and tree-hash retrieval, which is advantageous for large case bases.

Algorithms↗

PubMedDate not supplied

Technical aspects of internet-based knowledge presentation in radiotherapy.

Three-dimensional radiotherapy planning is a complex and time-consuming optimization process which requires much experience. To simplify and to speed up the process of treatment planning as well as to exchange experience and therapeutic knowledge, the department of Medical Physics at the German Cancer Research Centre (DKFZ) in Heidelberg is developing an Internet-based 3D Radiotherapy planning and Information System (IRIS). IRIS designed internet-based client-server application, implemented using Java, CORBA and PVM. The concept of IRIS combines the functionality of an interactive tutorial with a discussion forum, teleconferencing tool and an atlas of dose distributions. Furthermore an integral knowledge-based system provides automatically generated, preoptimized treatment plans. This paper explains the technical design of the system and gives an overview of experiences gained by the technical realization of a first prototype using currently available internet technology. The prototype is currently running for testing in the intranet of DKFZ.

Artificial Intelligence↗

PubMed2005

Data pre-processing in liquid chromatography-mass spectrometry-based proteomics.

MOTIVATION: In a liquid chromatography-mass spectrometry (LC-MS)-based expressional proteomics, multiple samples from different groups are analyzed in parallel. It is necessary to develop a data mining system to perform peak quantification, peak alignment and data quality assurance. RESULTS: We have developed an algorithm for spectrum deconvolution. A two-step alignment algorithm is proposed for recognizing peaks generated by the same peptide but detected in different samples. The quality of LC-MS data is evaluated using statistical tests and alignment quality tests. AVAILABILITY: Xalign software is available upon request from the author.

Algorithms↗

PubMed2001

Modeling data and knowledge in the EON guideline architecture.

Compared to guideline representation formalisms, data and knowledge modeling for clinical guidelines is a relatively neglected area. Yet it has enormous impact on the format and expressiveness of decision criteria that can be written, on the inferences that can be made from patient data, on the ease with which guidelines can be formalized, and on the method of integrating guideline-based decision-support services into implementation sites' information systems. We clarify the respective roles that data and knowledge modeling play in providing patient-specific decision support based on clinical guidelines. We show, in the context of the EON guideline architecture, how we use the Protégé-2000 knowledge-engineering environment to build (1) a patient-data information model, (2) a medical-specialty model, and (3) a guideline model that formalizes the knowledge needed to generate recommendations regarding clinical decisions and actions. We show how the use of such models allows development of alternative decision-criteria languages and allows systematic mapping of the data required for guideline execution from patient data contained in electronic medical record systems.

Artificial Intelligence↗

PubMed1992

Knowledge-based decision support for patient monitoring in cardioanesthesia.

An approach to generating 'intelligent alarms' is presented that aggregates many information items, i.e. measured vital signs, recent medications, etc., into state variables that more directly reflect the patient's physiological state. Based on these state variables the described decision support system AES-2 also provides therapy recommendations. The assessment of the state variables and the generation of therapeutic advice follow a knowledge-based approach. Aspects of uncertainty, e.g. a gradual transition between 'normal' and 'below normal', are considered applying a fuzzy set approach. Special emphasis is laid on the ergonomic design of the user interface, which is based on color graphics and finger touch input on the screen. Certain simulation techniques considerably support the design process of AES-2 as is demonstrated with a typical example from cardioanesthesia.

Anesthesia↗