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PubMedDate not supplied

Novel statistical approach for primary high-throughput screening hit selection.

The standard activity threshold-based method (the "top X" approach), currently widely used in the high-throughput screening (HTS) data analysis, is ineffective at identifying good-quality hits. We have proposed a novel knowledge-based statistical approach, driven by the hidden structure-activity relationship (SAR) within a screening library, for primary hit selection. Application to an in-house ultrahigh-throughput screening (uHTS) campaign has demonstrated it can directly identify active scaffolds containing valuable SAR information with a greatly improved confirmation rate compared to the standard "top X" method (from 55% to 85%). This approach may help produce high-quality leads and expedite the hit-to-lead process in drug discovery.

Algorithms↗

PubMed1992

The Comprehensive Assessment of Symptoms and History (CASH). An instrument for assessing diagnosis and psychopathology.

The Comprehensive Assessment of Symptoms and History was developed for research studies of schizophrenia spectrum conditions and affective spectrum conditions. It is designed to provide a comprehensive information base concerning current and past signs and symptoms, premorbid functioning, cognitive functioning, sociodemographic status, treatment, and course of illness. Because the information base is broad, it is not wedded to a specific diagnostic system but rather permits clinicians and investigators to make diagnoses using a wide range of systems, including Research Diagnostic Criteria, DSM-III, DSM-III-R, and the International Classification of Diseases. Given the fact that disorders in psychiatry are not defined at the etiological or pathophysiological level, diagnostic criteria are prone to ongoing revision as our knowledge base changes. Research strategies suggest that investigators should maintain a flexible database to permit them to adapt to changes in diagnostic systems, to do comparative nosological studies, and, ultimately, to develop new diagnostic systems based on knowledge concerning the underlying neurobiological nature of disorders. Because it provides a comprehensive information base, the Comprehensive Assessment of Symptoms and History facilitates research of this type. Extensive developmental work has been done with the Comprehensive Assessment of Symptoms and History, including interrater and test-retest reliability studies, validity studies, training programs, and data entry programs.

Databases, Factual↗

PubMed2004

What does it take to transform mental health knowledge into workplace practice? Towards a theory of action.

The purpose of this discussion paper is to consider the question of a knowledge base that might undergird a systematic approach to transforming mental health knowledge into workplace practice. Drawing on a range of systems-change and related research, the paper begins by contrasting the nature of "workplace" as opposed to "mental health knowledge" systems. On the basis of the Luhmann's concepts, these systems are cast as fundamentally being determined by the types of communication in which they are engaged (business about business matters, and mental health about mental health matters). For information from one to be adopted by the other requires the translation of mental health concepts into language understood by the workplace, by people capable of understanding both. The paper then examines the importance of determining a vision of desired outcome from such knowledge transfer. What is the desired outcome? A workplace free of mental health problems? The role of both values and existing knowledge in determining these is outlined, along with the importance of engaging the most immediately involved actors in developing the vision. Because valid and reliable knowledge is central to the task, a framework is set out in which the most immediately relevant research findings might be considered in relation to each other. Three categories of knowledge are proposed: employer-led preventive measures, employee-focused workplace interventions and community-based resources supportive of workplaces. Knowledge drawn from summative analyses of existing research is matched against these three categories to illustrate the potential for guiding both implementation and research decision making.The final section draws together the key elements of an active approach to promoting and supporting knowledge transformation from mental health research to workplaces.

Health Promotion↗

PubMedDate not supplied

Case-based reasoning algorithms applied in a medical acquisition tool.

The knowledge of clinical medicine can, efficiently and effectively, be elicited and encoded automatically as cases. The developed knowledge base often contains some redundancy. The cost can be tolerated as it affects neither the performance of the system nor the integrity of the knowledge. The advantages are simplicity in development and reliability in performance.

Algorithms↗

PubMed2002

Shape-based cortical surface segmentation for visualization brain mapping.

We describe a knowledge-based approach to cortical surface segmentation that uses learned knowledge of the overall shape and range of variation of the cortex (excluding the detailed gyri and sulci) to guide the search for the grey-CSF boundary in a structural MRI image volume. The shape knowledge is represented by a radial surface model, which is a type of geometric constraint network (GCN) that we hypothesize can represent shape by networks of locally interacting constraints. The shape model is used in a protocol for visualization-based mapping of cortical stimulation mapping (CSM) sites onto the brain surface, prior to integration with other mapping modalities or as input to existing surface analysis and reconfiguration programs. Example results are presented for CSM data related to language organization in the cortex, but the methods should be applicable to other situations where a realistic visualization of the brain surface, as seen at neurosurgery, is desired.

Brain Mapping↗

PubMed2006

A hybrid approach to shape-based interpolation of stereotactic atlases of the human brain.

Stereotactic human brain atlases, either in print or electronic form, are useful not only in functional neurosurgery, but also in neuroradiology, human brain mapping, and neuroscience education. The existing atlases represent structures on 2D plates taken at variable, often large intervals, which limit their applications. To overcome this problem, we propose a hybrid interpolation approach to build high-resolution brain atlases from the existing ones. In this approach, all section regions of each object are grouped into two types of components: simple and complex. A NURBS-based method is designed for interpolation of the simple components, and a distance map-based method for the complex components. Once all individual objects in the atlas are interpolated, the results are combined hierarchically in a bottom-up manner to produce the interpolation of the entire atlas. In the procedure, different knowledge-based and heuristic strategies are used to preserve various topological relationships. The proposed approach has been validated quantitatively and used for interpolation of two stereotactic brain atlases: the Talairach-Tournoux atlas and Schaltenbrand-Wahren atlas. The interpolations produced are of high resolution and feature high accuracy, 3D consistency, smooth surface, and preserved topology. They potentially open new applications for electronic stereotactic brain atlases, such as atlas reformatting, accurate 3D display, and 3D nonlinear warping against normal and pathological scans. The proposed approach is also potentially useful in other applications, which require interpolation and 3D modeling from sparse and/or variable intersection interval data. An example of 3D modeling of an infarct from MR diffusion images is presented.

Algorithms↗

PubMed2005

Development and validation of XML-based calculations within order sets.

We have developed two XML Schemas to support the implementation of calculations within XML-based order sets. The models support the representation of variable-based algorithms and include data elements designed to support ancillary functions such as input range checking, rounding, and minimum/maximum value constraints. Two clinicians successfully authored 57 unique calculated orders derived from a set of 11 calculations using the models within our authoring environment. The resultant knowledge base content was subsequently tested and found to produce the desired results within the electronic physician order entry environment.

Algorithms↗

PubMed2006

Semantic interoperability--HL7 Version 3 compared to advanced architecture standards.

OBJECTIVES: To meet the challenge for high quality and efficient care, highly specialized and distributed healthcare establishments have to communicate and co-operate in a semantically interoperable way. Information and communication technology must be open, flexible, scalable, knowledge-based and service-oriented as well as secure and safe. METHODS: For enabling semantic interoperability, a unified process for defining and implementing the architecture, i.e. structure and functions of the cooperating systems' components, as well as the approach for knowledge representation, i.e. the used information and its interpretation, algorithms, etc. have to be defined in a harmonized way. Deploying the Generic Component Model, systems and their components, underlying concepts and applied constraints must be formally modeled, strictly separating platform-independent from platform-specific models. RESULTS: As HL7 Version 3 claims to represent the most successful standard for semantic interoperability, HL7 has been analyzed regarding the requirements for model-driven, service-oriented design of semantic interoperable information systems, thereby moving from a communication to an architecture paradigm. The approach is compared with advanced architectural approaches for information systems such as OMG's CORBA 3 or EHR systems such as GEHR/openEHR and CEN EN 13606 Electronic Health Record Communication. CONCLUSION: HL7 Version 3 is maturing towards an architectural approach for semantic interoperability. Despite current differences, there is a close collaboration between the teams involved guaranteeing a convergence between competing approaches.

Computer Communication Networks↗

PubMed1993

Developing a standard data structure for medical language--the SNOMED proposal.

The Systematized Nomenclature of Medicine, Third Edition, SNOMED International, is a comprehensive structured nomenclature of human and veterinary medicine, the terms of which are detailed, fine grained and semantically typed. Terms are assigned to eleven independent modules (fields), each of which is systematized. Terms may be linked to on another to represent complex entities or manifestations or alternately complex terms dissected into their elemental parts. Terms are illustrated utilizing a frame representation. Efforts are in progress to build both a conceptual graph and a frame-based semantic network encompassing each SNOMED term, effectively building a knowledge base. In this way, the knowledge contained in each alphanumeric representation is made explicit. SNOMED is a linked data structure capable of faithfully representing the activities, observations and diagnoses found in the medical record in a computer processable form.

Animals↗

PubMed2005

Classification of error in anatomic pathology: a proposal for an evidence-based standard.

Error in anatomic pathology (EAP) is an appropriate problem to consider using the disease model with which all pathologists are familiar. In analogy to medical diseases, diagnostic errors represent a complex constellation of often-baffling deviations from the "normal" condition. Ideally, one would wish to approach such "diseases of diagnosis" with effective treatments or preventative measures, but interventions in the absence of a clear understanding of pathogenesis are often ineffective or even harmful. Medical therapy has its history of "bleeding and purging," and error-prevention has a history of "blaming and shaming." The urge to take action in dealing with either medical illnesses or diagnostic failings is, of course, admirable. However, the principle of primum non nocere should guide one's action in both circumstances. The first step in using the disease model to address EAP is the development of a valid taxonomy to allow for grouping together of abnormalities that have a similar pathogenesis. It is apparent that disease categories such as "tumor" are not valuable until they are further refined by precise and accurate classification. Likewise, "error" is an impossibly broad concept that must be parsed into meaningful subcategories before it can be understood with sufficient clarity to be prevented. One important EAP subtype that has been particularly difficult to understand and classify is knowledge-based interpretative (KBI) error. Not only is the latter sometimes confused with distinctly different error types such as human lapses, but there is danger of mistaking system-wide problems (eg, imprecise or inaccurate diagnostic criteria) for the KBI errors of individual pathologists. This paper presents a theoretically-sound taxonomic system for classification of error that can be used for evidence-based categorization of individual cases. Any taxonomy of error in medicine must distinguish between the various factors that may produce mistakes, and importantly, whether they are individual, small system (e.g., my histology laboratory), or big system (e.g., published diagnostic criteria). Because no overarching governing agency exists to coordinate this initiative, the recognition of need and effective implementation of EAP counter-measures must emanate from our specialty group itself.

Bias↗

PubMed2006

Peroxisome targeting signal 1: is it really a simple tripeptide?

Originally, the peroxisomal targeting signal 1 (PTS1) was defined as a tripeptide at the C-terminus of proteins prone to be imported into the peroxisomal matrix. The corresponding receptor PEX5 initiates the translocation of proteins by identifying potential substrates via their C-termini and trapping PTS1s through remodeling of its TPR domain. Thorough studies on the interaction between PEX5 and PTS1 as well as sequence-analytic tools revealed the influence of amino acid residues further upstream of the ultimate tripeptide. Altogether, PTS1s should be defined as dodecamer sequences at the C-terminal ends of proteins. These sequences accommodate physical contacts with both the surface and the binding cavity of PEX5 and ensure accessibility of the extreme C-terminus. Knowledge-based approaches in applied Bioinformatics provide reliable tools to accurately predict the peroxisomal location of proteins not yet determined experimentally.

Amino Acid Motifs↗

PubMed1999

Nature of clinical practice for specialists in orthopaedic physical therapy.

Clinical specialization is part of physical therapy's continued development as a profession. Clinical specialization in physical therapy has evolved with little discussion of how specialization is related to the development of professional expertise. The purposes of this paper were to compare the identified clinical competencies in orthopaedic physical therapy to selected clinical reasoning models and expertise development models in physical therapy and interpret these comparisons in light of current theoretical work in expertise. Descriptive content analysis using results from the 1993 Practice Analysis for Orthopaedic Physical Therapy Certified Specialists was done to link attributes identified in 3 selected theoretical models of clinical decision making and practice. Survey materials were linked to theories by use of a binary index (yes/no) of whether theoretical concepts were present or absent in the survey results. The attributes that characterize an expert physical therapy practitioner involve clinical reasoning, and the ability to teach patients. The skills of a master clinician were based not just on the application of knowledge, but also on thinking and reasoning that occurs with experience. We propose that knowledge is gained through the clinician's thinking and reasoning during practice which results in a transformation or change in the clinician's knowledge base. Describing the clinical specialization process in the context of expert theory provides a strong foundation for the specialization process in physical therapy.

California↗

PubMedDate not supplied

Comparing the performance of FLUFF-BALL to SEAL-CoMFA with a large diverse estrogen data set: from relevant superpositions to solid predictions.

In this work a template-based molecular mechanistic superposition algorithm FLUFF (Flexible Ligand Unified Force Field) and an accompanying local coordinate QSAR method BALL (Boundless Adaptive Localized Ligand) are validated against the benchmark techniques SEAL (Steric and Electrostatic Alignment) and CoMFA (Comparative Molecular Field Analysis) using a large diverse set of 245 xenoestrogens extracted from the EDKB (Endocrine Disruptor Knowledge Base) maintained by NCTR (National Centre for Toxicological Research). The results indicate that FLUFF is capable of generating relevant superpositions not only for BALL but also for CoMFA, as both techniques give predictive QSAR models. When the BALL and CoMFA methods are compared, it is clear that the BALL algorithm met or even exceeded the results of the standard 3D-QSAR method CoMFA using alignments either from the tailor-made superposition technique FLUFF or the reference method SEAL. The FLUFF-BALL method can be easily automated, and it is computationally light, providing thus a good computational "sieve" capable of fast screening of large molecule libraries.

Algorithms↗

PubMed2006

Meeting the criteria of a nursing diagnosis classification: Evaluation of ICNP, ICF, NANDA and ZEFP.

BACKGROUND: Few studies described nursing diagnosis classification criteria and how classifications meet these criteria. OBJECTIVES: The purpose was to identify criteria for nursing diagnosis classifications and to assess how these criteria are met by different classifications. DESIGN/METHODS: First, a literature review was conducted (N=50) to identify criteria for nursing diagnoses classifications and to evaluate how these criteria are met by the International Classification of Nursing Practice (ICNP), the International Classification of Functioning, Disability and Health (ICF), the International Nursing Diagnoses Classification (NANDA), and the Nursing Diagnostic System of the Centre for Nursing Development and Research (ZEFP). Using literature review based general and specific criteria, the principal investigator evaluated each classification, applying a matrix. Second, a convenience sample of 20 nursing experts from different Swiss care institutions answered standardized interview forms, querying current national and international classification state and use. RESULTS: The first general criterion is that a diagnosis classification should describe the knowledge base and subject matter for which the nursing profession is responsible. ICNP) and NANDA meet this goal. The second general criterion is that each class fits within a central concept. The ICF and NANDA are the only two classifications built on conceptually driven classes. The third general classification criterion is that each diagnosis possesses a description, diagnostic criteria, and related etiologies. Although ICF and ICNP describe diagnostic terms, only NANDA fulfils this criterion. The analysis indicated that NANDA fulfilled most of the specific classification criteria in the matrix. The nursing experts considered NANDA to be the best-researched and most widely implemented classification in Switzerland and internationally. CONCLUSIONS: The international literature and the opinion of Swiss expert nurses indicate that-from the perspective of classifying comprehensive nursing diagnoses-NANDA should be recommended for nursing practice and electronic nursing documentation. Study limitations and future research needs are discussed.

Attitude of Health Personnel↗

PubMed2002

Injury biomechanics for aiding in the diagnosis of abusive head trauma.

Much of what is understood as potential for injury is based in what has been observed clinically. This knowledge base is critical for decision making but has inherent and important limitations. Experimental studies investigating the influence of environmental factors, such as height of fall and surface type on injury potential, add important information, but also have inherent limitations. Important trends and predictions of probable injury can be studied but inference to a specific child's injuries is difficult because of unaccounted for contributing factors of injury risk. Such factors include muscle contraction, protective reflexes, and specific tissue response to trauma forces. Additional biomechanical research is needed to bridge the gap between clinical observations and experimental predictions. The specific and unique perspective of the neurosurgeon is a critical piece in differentiating accidental and nonaccidental head injury with experience and reason as the basis of the conclusion. Do the physics of the injury match the mechanistic principals of the described injury event? Could all of the injuries result from the event? Is it plausible that these set of injuries occurred from the described event based on the [table: see text] physician's experience and the current scientific understanding of injury biomechanics? Do the mechanical forces of the reported mechanism and injuries match? To determine that an explanation is plausible requires consideration of all the facts and injuries, consideration of the described behavior, and consistency with the neurologic status. These facts of the case are compared with medical knowledge and the learned experience of the neurosurgeon. The answer to the question "is it possible?" is based on clinical experience and objective reasoning. Rather than a black box question and answer based in unrealistic probability, the answer is based on the facts of the case and physical principles that govern biomechanics and resultant injuries.

Biomechanical Phenomena↗

PubMed2000

A gut feeling? Intuition and critical care nursing.

As nurses, we are knowledgeable about nursing and able, immediately and intuitively, to identify the needs and demands of a given situation. Experienced nurses practise intuitively by virtue of having developed, through critical thought, a deeply grounded knowledge base that can be applied in daily practice. Each gains knowledge about nursing practice in such a way that every clinical experience becomes a lesson which informs the next experience. There is continued debate over the domain of nursing knowledge, where it originates and to whom it belongs. Much of nursing knowledge has emerged from the practice of other professions. There now appears to be an increasing focus within today's modern healthcare environment on the importance of measurable outcomes and the need to predict the consequences of all interventions. The strength of our intuition often urges us to do something more for the patient. When we as nurses report our intuitions, subjective feelings are often at odds with the objective signs and symptoms. Nurses have made great strides in recognizing, analysing and teaching concepts related to logical, rational decision-making. It is imperative, however, also to recognize and teach the concepts related to the intuitive and precognitive components of making decisions in clinical practice.

Attitude of Health Personnel↗

PubMed2004

Physical scoring function based on AMBER force field and Poisson-Boltzmann implicit solvent for protein structure prediction.

A well-behaved physics-based all-atom scoring function for protein structure prediction is analyzed with several widely used all-atom decoy sets. The scoring function, termed AMBER/Poisson-Boltzmann (PB), is based on a refined AMBER force field for intramolecular interactions and an efficient PB model for solvation interactions. Testing on the chosen decoy sets shows that the scoring function, which is designed to consider detailed chemical environments, is able to consistently discriminate all 62 native crystal structures after considering the heteroatom groups, disulfide bonds, and crystal packing effects that are not included in the decoy structures. When NMR structures are considered in the testing, the scoring function is able to discriminate 8 out of 10 targets. In the more challenging test of selecting near-native structures, the scoring function also performs very well: for the majority of the targets studied, the scoring function is able to select decoys that are close to the corresponding native structures as evaluated by ranking numbers and backbone Calpha root mean square deviations. Various important components of the scoring function are also studied to understand their discriminative contributions toward the rankings of native and near-native structures. It is found that neither the nonpolar solvation energy as modeled by the surface area model nor a higher protein dielectric constant improves its discriminative power. The terms remaining to be improved are related to 1-4 interactions. The most troublesome term is found to be the large and highly fluctuating 1-4 electrostatics term, not the dihedral-angle term. These data support ongoing efforts in the community to develop protein structure prediction methods with physics-based potentials that are competitive with knowledge-based potentials.

Algorithms↗

PubMed2006

Potential for assessing quality of protein structure based on contact number prediction.

We developed a novel knowledge-based residue environment potential for assessing the quality of protein structures in protein structure prediction. The potential uses the contact number of residues in a protein structure and the absolute contact number of residues predicted from its amino acid sequence using a new prediction method based on a support vector regression (SVR). The contact number of an amino acid residue in a protein structure is defined by the number of residues around a given residue. First, the contact number of each residue is predicted using SVR from an amino acid sequence of a target protein. Then, the potential of the protein structure is calculated from the probability distribution of the native contact numbers corresponding to the predicted ones. The performance of this potential is compared with other score functions using decoy structures to identify both native structure from other structures and near-native structures from nonnative structures. This potential improves not only the ability to identify native structures from other structures but also the ability to discriminate near-native structures from nonnative structures.

Algorithms↗