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Träfflista för sökning "WFRF:(Ahmed Mobyen Uddin) srt2:(2011)"

Sökning: WFRF:(Ahmed Mobyen Uddin) > (2011)

  • Resultat 1-7 av 7
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1.
  • Ahmed, Mobyen Uddin, 1976-, et al. (författare)
  • A Case-Based Retrieval System for Post-Operative Pain Treatment
  • 2011
  • Konferensbidrag (refereegranskat)abstract
    • This paper presents a clinical decision support system based on case-basedretrieval approach to assist physicians in post-operative pain treatment. Here,the cases are formulated by combining regular features and features using anumerical visual analogue scale (NVAS) through a questionnaire. Featureabstraction is done both in problem and outcome description of a case in order toreduce the number of attributes. The system retrieves most similar cases with theiroutcomes. The outcome of each case brings benefits for physicians since it presentsboth severity and fast recovery by the applied treatment in post-operative patients.Therefore, we have introduced a two-layer case structure i.e., solution is the firstlayer and outcome is the second layer that better suits this medical application. Inthe system, the solution presents the treatment and the outcome contains recoveryinformation of a patient, something physicians are interested in, especially the riskof side effects and complications.
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2.
  • Ahmed, Mobyen Uddin, et al. (författare)
  • A Multi-Module Case Based Biofeedback System for Stress Treatment
  • 2011
  • Ingår i: Artificial Intelligence in Medicine. - : Elsevier BV. - 0933-3657 .- 1873-2860. ; 51:2, s. 107-115
  • Tidskriftsartikel (refereegranskat)abstract
    • Biofeedback is today a recognized treatment method for a number of physical and psychological problems. Experienced clinicians often achieve good results in these areas and their success largely builds on many years of experience and often thousands of treated patients. Unfortunately many of the areas where biofeedback is used are very complex, e.g. diagnosis and treatment of stress. Less experienced clinicians may even have difficulties to initially classify the patient correctly. Often there are only a few experts available to assist less experienced clinicians. To reduce this problem we propose a computer assisted biofeedback system helping in classification, parameter setting and biofeedback training. By adopting a case based approach in a computer-based biofeedback system, decision support can be offered to less experienced clinicians and provide a second opinion to experts. We explore how such a system may be designed and validate the approach in the area of stress where the system assists in the classification, parameter setting and finally in the training. In a case study we show that the case based biofeedback system outperforms novice clinicians based on a case library of cases authorized by an expert.
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3.
  • Ahmed, Mobyen Uddin, 1976- (författare)
  • A Multimodal Approach for Clinical Diagnosis and Treatment
  • 2011
  • Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
    • A computer-aided Clinical Decision Support System (CDSS) for diagnosis and treatment often plays a vital role and brings essential benefits for clinicians. Such a CDSS could function as an expert for a less experienced clinician or as a second option/opinion of an experienced clinician to their decision making task. Nevertheless, it has been a real challenge to design and develop such a functional system where accuracy of the system performance is an important issue. This research work focuses on development of intelligent CDSS based on a multimodal approach for diagnosis, classification and treatment in medical domains i.e. stress and post-operative pain management domains. Several Artificial Intelligence (AI) techniques such as Case-Based Reasoning (CBR), textual Information Retrieval (IR), Rule-Based Reasoning (RBR), Fuzzy Logic and clustering approaches have been investigated in this thesis work. Patient’s data i.e. their stress and pain related information are collected from complex data sources for instance, finger temperature measurements through sensor signals, pain measurements using a Numerical Visual Analogue Scale (NVAS), patient’s information from text and multiple choice questionnaires. The proposed approach considers multimedia data management to be able to use them in CDSSs for both the domains. The functionalities and performance of the systems have been evaluated based on close collaboration with experts and clinicians of the domains. In stress management, 68 measurements from 46 subjects and 1572 patients’ cases out of ≈4000 in post-operative pain have been used to design, develop and validate the systems. In the stress management domain, besides the 68 measurement cases, three trainees and one senior clinician also have been involved in order to conduct the experimental work. The result from the evaluation shows that the system reaches a level of performance close to the expert and better than the senior and trainee clinicians. Thus, the proposed CDSS could be used as an expert for a less experienced clinician (i.e. trainee) or as a second option/opinion for an experienced clinician (i.e. senior) to their decision making process in stress management. In post-operative pain treatment, the CDSS retrieves and presents most similar cases (e.g. both rare and regular) with their outcomes to assist physicians. Moreover, an automatic approach is presented in order to identify rare cases and 18% of cases from the whole cases library i.e. 276 out of 1572 are identified as rare cases by the approach. Again, among the rare cases (i.e. 276), around 57.25% of the cases are classified as ‘unusually bad’ i.e. the average pain outcome value is greater or equal to 5 on the NVAS scale 0 to 10. Identification of rear cases is an important part of the PAIN OUT project and can be used to improve the quality of individual pain treatment.
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4.
  • Ahmed, Mobyen Uddin, et al. (författare)
  • Bibliometric Profiling of a Group: A Discussion on Different Indicators
  • 2011
  • Rapport (övrigt vetenskapligt/konstnärligt)abstract
    • Now-a-days in some advanced countries bibliometric profiling plays a vital role when making decision on promotion, fund allocation and award prizes. Accurate identification of this is important since it is becoming important to assess scientific output for a researcher or a group of researcher. This paper presents and discusses several most common indicators of bibliometric profiling together with h- and g-indexes. A case study has been conducted on 101 scientific articles with three most well known search engines. The study results using several indicators are presented in this report.
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5.
  • Ahmed, Mobyen Uddin, 1976-, et al. (författare)
  • Mining Rare Cases in Post-Operative Pain by Means of Outlier Detection
  • 2011
  • Ingår i: IEEE Symposium on Signal Processing and Information Technology (ISSPIT) 2011. - : IEEE. - 9781467307536 ; , s. 35-41
  • Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
    • Rare cases are often interesting for healthprofessionals, physicians, researchers and clinicians in order toreuse and disseminate experiences in healthcare. However,mining, i.e. identification of rare cases in electronic patientrecords, is non-trivial for information technology. This paperinvestigates a number of well-known clustering algorithms andfinally applies a 2nd order clustering approach by combining theFuzzy C-means algorithm with the Hierarchical one. Theapproach is used in order to identify rare cases from 1572patient cases in the domain of post-operative pain management.The results show that the approach enables identification of rarecases in the domain of post-operative pain management and 18%of cases are identified as rare case.
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6.
  • Begum, Shahina, et al. (författare)
  • Case-Based Reasoning Systems in the Health Sciences : A Survey of Recent Trends and Developments
  • 2011
  • Ingår i: IEEE transactions on systems, man and cybernetics. Part C, Applications and reviews. - 1094-6977 .- 1558-2442. ; 41:4, s. 421-434
  • Tidskriftsartikel (refereegranskat)abstract
    • The Health Sciences are, nowadays, one of the major application areas for case-based reasoning (CBR). The paper presents a survey of recent medical CBR systems based on a literature review and an e-mail questionnaire sent to the corresponding authors of the papers where these systems are presented. Some clear trends have been identified, such as multipurpose systems: more than half of the current medical CBR systems address more than one task. Research on CBR in the area is growing, but most of the systems are still prototypes and not available on the market as commercial products. However, many of the projects/systems are intended to be commercialized.
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7.
  • Begum, Shahina, et al. (författare)
  • K-NN Based Interpolation to Handle Artifacts for Heart Rate Variability Analysis
  • 2011
  • Ingår i: IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2011. - : IEEE. ; , s. 387-392
  • Konferensbidrag (refereegranskat)abstract
    • Heart rate variability (HRV) is a popular parameter for depicting activities of autonomous nervous system and helps to explain various physiological activities of the body. A small amount of artifacts can produce significant changes especially, for time domain HRV features. Manual correction of artifacts performed by visual inspection of the signal by experts is tedious and time consuming and often leads to incorrect result especially for long term recordings. Therefore, an automatic artifact removing approach that helps to provide clinically useful HRV analysis is valuable. This paper proposes an algorithm that detects and replaces artifacts from inter-beat interval (IBI) signal for HRV analysis. The detection is mainly based on windowing technique and interpolation is performed using the k-nearest neighbour (K-NN) algorithm. The experimental work shows a promising performance in handling artifacts for HRV analysis using electrocardiogram (ECG) sensor signal.
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  • Resultat 1-7 av 7

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