The Experts below are selected from a list of 8850 Experts worldwide ranked by ideXlab platform
Doeltgen, Sebastian H. - One of the best experts on this subject based on the ideXlab platform.
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Clinical reasoning and Hypothesis generation in expert clinical swallowing examinations
'Wiley', 2020Co-Authors: Mcallister Sue, Tedesco Helen, Kruger Samantha, Ward, Elizabeth C., Marsh Claire, Doeltgen, Sebastian H.Abstract:Background: A clinical swallow examination (CSE) provides integral information that informs the diagnostic decision-making process within dysphagia management. However, multiple studies have highlighted a high degree of reported variability within the CSE process. It has been hypothesized that such variability may be the result of the clinical reasoning process rather than poor practices. Aims: To elucidate the nature of expert, speech–language therapists’ (SLTs) clinical reasoning during an initial bedside assessment of patients referred for suspected dysphagia in the acute care environment. Methods & Procedures: An exploratory ‘observation of practice’ qualitative methodology was used to achieve the aim. Four expert SLTs, from two clinical services, completed CSEs with 10 new referrals for suspected dysphagia. All assessments were video-recorded, and within 30 min of completing the CSE, a video-stimulated ‘think aloud’ semi-structured interview was conducted in which the SLT was prompted to articulate their clinical reasoning at each stage of the CSE. Three types of concept maps were generated based on this video and interview content: a descriptive concept map, a reasoning map and a Hypothesis map. Patterns that consistently characterized the assessment process were identified, including the overall structure; types of reasoning (Inductive versus deductive), facts (i.e., clinical information) drawn upon; and outcomes of the process (diagnosis and recommendations). Interview content was examined to identify types of expert reasoning strategies using during the CSE. Outcomes & Results: SLTs’ approach to clinical assessment followed a consistent structure, with data gathered pre-bedside, during the patient interview and direct assessment before a management recommendation was made. Within this structure, SLTs engaged in an iterative approach with Inductive Hypothesis-generating and deductive Hypothesis-testing, with each decision-making pathway individually tailored and informed by patient-specific facts collected during the assessment. Clinical assessment was primarily geared towards management of an initial acute presentation with less focus on formulating a diagnostic statement. Conclusions & Implications: Variability in reported dysphagia practice is likely the result of a patient-centred assessment process characterized by iterative cycles of fact-gathering in order to generate and test clinical hypotheses. This has implications for the development of novel assessment tools, as well as professional development and education of novice SLTs. What this paper adds What is already known on the subject CSE practices are reportedly variable, which has led to calls for more stringent, standardized assessment tools. Emerging evidence suggests that this variation is non-random, but may arise from clinical reasoning processes. What this paper adds to existing knowledge We directly observed expert SLTs conducting CSEs and identified patterns in practice that were consistent across all CSEs evaluated. These patterns were consistent in structure, whereas the content of the assessment items varied and was tailored to individual patient presentation. Overall, expert SLTs engaged in balanced cycles of Inductive Hypothesis generation and deductive Hypothesis-testing, a hallmark of good clinical assessment and practice. What are the potential or actual clinical implications of this work? Ensuring quality CSE requires a more nuanced approach that considers the role of clinical reasoning in SLTs’ decision-making and the potential unintended negative consequences of standardized assessment tools
Chung Yang Huang - One of the best experts on this subject based on the ideXlab platform.
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Property-specific sequential invariant extraction for SAT-based unbounded model checking
2011 IEEE ACM International Conference on Computer-Aided Design (ICCAD), 2011Co-Authors: Cheng-yin Wu, Chung Yang HuangAbstract:In this paper, we propose a property-specific sequential invariant extraction algorithm to improve the performance of the SAT-based Unbounded Modeling Checkers (UMCs). By analyzing the property-related predicates and their corresponding high-level design constructs such as FSMs and counters, we can quickly identify the sequential invariants that are useful in improving the property proving capabilities. We utilize these sequential invariants to refine the Inductive Hypothesis in induction-based UMCs, and to improve the accuracy of reachable state approximation in interpolation-based UMCs. The experimental results show that our tool can outperform a state-of-the-art UMC in most cases, especially for the difficult true properties.
Mcallister Sue - One of the best experts on this subject based on the ideXlab platform.
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Clinical reasoning and Hypothesis generation in expert clinical swallowing examinations
'Wiley', 2020Co-Authors: Mcallister Sue, Tedesco Helen, Kruger Samantha, Ward, Elizabeth C., Marsh Claire, Doeltgen, Sebastian H.Abstract:Background: A clinical swallow examination (CSE) provides integral information that informs the diagnostic decision-making process within dysphagia management. However, multiple studies have highlighted a high degree of reported variability within the CSE process. It has been hypothesized that such variability may be the result of the clinical reasoning process rather than poor practices. Aims: To elucidate the nature of expert, speech–language therapists’ (SLTs) clinical reasoning during an initial bedside assessment of patients referred for suspected dysphagia in the acute care environment. Methods & Procedures: An exploratory ‘observation of practice’ qualitative methodology was used to achieve the aim. Four expert SLTs, from two clinical services, completed CSEs with 10 new referrals for suspected dysphagia. All assessments were video-recorded, and within 30 min of completing the CSE, a video-stimulated ‘think aloud’ semi-structured interview was conducted in which the SLT was prompted to articulate their clinical reasoning at each stage of the CSE. Three types of concept maps were generated based on this video and interview content: a descriptive concept map, a reasoning map and a Hypothesis map. Patterns that consistently characterized the assessment process were identified, including the overall structure; types of reasoning (Inductive versus deductive), facts (i.e., clinical information) drawn upon; and outcomes of the process (diagnosis and recommendations). Interview content was examined to identify types of expert reasoning strategies using during the CSE. Outcomes & Results: SLTs’ approach to clinical assessment followed a consistent structure, with data gathered pre-bedside, during the patient interview and direct assessment before a management recommendation was made. Within this structure, SLTs engaged in an iterative approach with Inductive Hypothesis-generating and deductive Hypothesis-testing, with each decision-making pathway individually tailored and informed by patient-specific facts collected during the assessment. Clinical assessment was primarily geared towards management of an initial acute presentation with less focus on formulating a diagnostic statement. Conclusions & Implications: Variability in reported dysphagia practice is likely the result of a patient-centred assessment process characterized by iterative cycles of fact-gathering in order to generate and test clinical hypotheses. This has implications for the development of novel assessment tools, as well as professional development and education of novice SLTs. What this paper adds What is already known on the subject CSE practices are reportedly variable, which has led to calls for more stringent, standardized assessment tools. Emerging evidence suggests that this variation is non-random, but may arise from clinical reasoning processes. What this paper adds to existing knowledge We directly observed expert SLTs conducting CSEs and identified patterns in practice that were consistent across all CSEs evaluated. These patterns were consistent in structure, whereas the content of the assessment items varied and was tailored to individual patient presentation. Overall, expert SLTs engaged in balanced cycles of Inductive Hypothesis generation and deductive Hypothesis-testing, a hallmark of good clinical assessment and practice. What are the potential or actual clinical implications of this work? Ensuring quality CSE requires a more nuanced approach that considers the role of clinical reasoning in SLTs’ decision-making and the potential unintended negative consequences of standardized assessment tools
Kenneth L Mcmillan - One of the best experts on this subject based on the ideXlab platform.
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symbolic model checking an approach to the state explosion problem
Ph. D. Thesis Carnegie Mellon University, 1992Co-Authors: Kenneth L McmillanAbstract:Finite state models of concurrent systems grow exponentially as the number of components of the system increases. This is known widely as the state explosion problem in automatic verification, and has limited finite state verification methods to small systems. To avoid this problem, a method called symbolic model checking is proposed and studied. This method avoids building a state graph by using Boolean formulas to represent sets and relations. A variety of properties characterized by least and greatest fixed points can be verified purely by manipulations of these formulas using Ordered Binary Decision Diagrams. Theoretically, a structural class of sequential circuits is demonstrated whose transition relations can be represented by polynomial space OBDDs, though the number of states is exponential. This result is born out by experimental results on example circuits and systems. The most complex of these is the cache consistency protocol of a commercial distributed multiprocessor. The symbolic model checking technique revealed subtle errors in this protocol, resulting from complex execution sequences that would occur with very low probability in random simulation runs. In order to model the cache protocol, a language was developed for describing sequential circuits and protocols at various levels of abstraction. This language has a synchronous dataflow semantics, but allows nondeterminism and supports interleaving processes with shared variables. A system called SMV can automatically verify programs in this language with respect to temporal logic formulas, using the symbolic model checking technique. A technique for proving properties of Inductively generated classes of finite state systems is also developed. The proof is checked automatically, but requires a user supplied process called a process invariant to act as an Inductive Hypothesis. An invariant is developed for the distributed cache protocol, allowing properties of systems with an arbitrary number of processors to be proved. Finally, an alternative method is developed for avoiding the state explosion in the case of asynchronous control circuits. This technique is based on the unfolding of Petri nets, and is used to check for hazards in a distributed mutual exclusion circuit.
Cheng-yin Wu - One of the best experts on this subject based on the ideXlab platform.
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Property-specific sequential invariant extraction for SAT-based unbounded model checking
2011 IEEE ACM International Conference on Computer-Aided Design (ICCAD), 2011Co-Authors: Cheng-yin Wu, Chung Yang HuangAbstract:In this paper, we propose a property-specific sequential invariant extraction algorithm to improve the performance of the SAT-based Unbounded Modeling Checkers (UMCs). By analyzing the property-related predicates and their corresponding high-level design constructs such as FSMs and counters, we can quickly identify the sequential invariants that are useful in improving the property proving capabilities. We utilize these sequential invariants to refine the Inductive Hypothesis in induction-based UMCs, and to improve the accuracy of reachable state approximation in interpolation-based UMCs. The experimental results show that our tool can outperform a state-of-the-art UMC in most cases, especially for the difficult true properties.