5 results on '"Maane R"'
Search Results
2. A Novel Multiple-Instance Learning-Based Approach to Computer-Aided Detection of Tuberculosis on Chest X-Rays
- Author
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Melendez Rodriguez, J.C., Ginneken, B. van, Maduskar, P., Philipsen, R.H.H.M., Reither, K., Breuninger, M., Adetifa, I.M.O., Maane, R., Ayles, H., Sanchez, C.I., Melendez Rodriguez, J.C., Ginneken, B. van, Maduskar, P., Philipsen, R.H.H.M., Reither, K., Breuninger, M., Adetifa, I.M.O., Maane, R., Ayles, H., and Sanchez, C.I.
- Abstract
Contains fulltext : 154701.pdf (Publisher’s version ) (Open Access), In order to reach performance levels comparable to those of human experts, computer-aided detection (CAD) systems are typically optimized by means of a supervised learning approach that relies on large training databases comprising manually annotated lesions. However, manually outlining those lesions constitutes a difficult and time-consuming process that renders detailedly annotated data often difficult to obtain. In this paper, we investigate an alternative pattern classification approach, namely multiple-instance learning (MIL), that does not require such detailed information for a CAD system to be optimized. We have applied MIL to a CAD system aimed at detecting textural lesions associated with tuberculosis. Only the case (or image) condition (normal or abnormal), which was determined by radiological means, was required during training. Based upon the well-known miSVM technique, we propose a novel algorithm, specifically designed for our CAD application, that overcomes serious drawbacks of the former related to underestimation of the positive instances and costly iteration. The key of the proposed method is to use probability estimates instead of decision values to guide the MIL procedure. In addition, we include countermeasures that deal with the uncertainty resulting from instance relabeling. To show the advantages of our MIL-based approach as compared with a traditional supervised one, experiments with three different image databases were conducted. The area under the receiver operating characteristic curve was utilized as a performance measure. With the first database, for which training lesion annotations were available, the supervised system was not much better than our MILbased method (0:88 vs. 0:86). Thus, the proposed approach achieved highly competitive results without resorting to lesionlevel information and the associated annotation process. When evaluating the remaining databases, given their large difference with respect to the previous image set
- Published
- 2015
3. G270(P) Post-operative outcomes of gambian children and adolescents post valvular surgery for rheumatic heart disease
- Author
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Martin, K, Forrest, K, Jaiteh, L, Maane, R, and Anderson, S
- Abstract
AimsRheumatic heart disease (RHD) is a potentially debilitating and fatal condition with a high prevalence in low resource countries. The Gambia has many individuals with severe, symptomatic RHD but limited cardiology and no cardiothoracic surgical services. Charitable organisations fund surgery overseas for a minority. We aimed to review post-operative outcomes in this group.MethodsPaediatric RHD patients with documented pre- and post-operative management at our institution were included. Retrospective data from clinical records was collected on age, sex, HIV, HBV and sickle cell status, operation type, pre- and post-operative Ross scores and medication burden (table 1). For warfarinised patients, ‘percentage days within therapeutic range’ was calculated using the Rosendaal method.Results17 patients matched our inclusion criteria; 11 male, 6 female. Median age at surgery was 16 years. There was one death (cause: infective endocarditis). In total, 19 operations were performed involving 31 valve procedures; 7 metallic and 5 bioprosthetic valve replacements and 19 repairs.Abstract G270(P) Table 1Pre-operative median (IQR)Post-operative median (IQR)P valueRoss Score 2 (2–3) 1 (1–1) 0.013 Number of Pills per day 3 (2–5) 1 (0–2) 0.004 Daily Furosemide dose (mg) 20 (10–40) 0 (0–20) 0.242 Daily Spironolactone dose (mg) 25 (0–25) 0 (0–0) 0.075 Daily captopril dose (mg) 37.5 (5–50) 0 (0–50) 0.279 For the six warfarinised patients, median percentage days within target therapeutic range (TTR) was 40.2% and percentage of tests within TTR was 34.1%.ConclusionIn this small cohort of Gambian children and adolescents, cardiac surgery had a positive impact with significant effects on exercise tolerance and pill burden. Normal exercise tolerance following fifteen (78.9%) operations had positive social, economic and medical implications. However, there is a long-term risk of haemorrhage and thromboembolism in warfarinised patients given the low proportion of time in therapeutic range. Our evaluation highlights the challenges of working with adolescents around medication adherence, lack of alternatives to warfarin for young women of child bearing age and the need for high quality pre- and post-operative assessment and follow-up in low resource environments.
- Published
- 2018
- Full Text
- View/download PDF
4. A tuberculosis nationwide prevalence survey in Gambia, 2012.
- Author
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Adetifa IM, Kendall L, Bashorun A, Linda C, Omoleke S, Jeffries D, Maane R, Alorse BD, Alorse WD, Okoi CB, Mlaga KD, Kinteh MA, Donkor S, de Jong BC, Antonio M, and d'Alessandro U
- Subjects
- Adolescent, Adult, Aged, Aged, 80 and over, Cross-Sectional Studies, Female, Gambia epidemiology, Health Surveys, Humans, Male, Middle Aged, Mycobacterium tuberculosis, Prevalence, Sputum microbiology, Young Adult, Tuberculosis, Pulmonary diagnosis, Tuberculosis, Pulmonary epidemiology
- Abstract
Objective: To estimate the population prevalence of active pulmonary tuberculosis in Gambia., Methods: Between December 2011 and January 2013, people aged ≥ 15 years participating in a nationwide, multistage cluster survey were screened for active pulmonary tuberculosis with chest radiography and for tuberculosis symptoms. For diagnostic confirmation, sputum samples were collected from those whose screening were positive and subjected to fluorescence microscopy and liquid tuberculosis cultures. Multiple imputation and inverse probability weighting were used to estimate tuberculosis prevalence., Findings: Of 100 678 people enumerated, 55 832 were eligible to participate and 43 100 (77.2%) of those participated. A majority of participants (42 942; 99.6%) were successfully screened for symptoms and by chest X-ray. Only 5948 (13.8%) were eligible for sputum examination, yielding 43 bacteriologically confirmed, 28 definite smear-positive and six probable smear-positive tuberculosis cases. Chest X-ray identified more tuberculosis cases (58/69) than did symptoms alone (43/71). The estimated prevalence of smear-positive and bacteriologically confirmed pulmonary tuberculosis were 90 (95% confidence interval, CI: 53-127) and 212 (95% CI: 152-272) per 100 000 population, respectively. Tuberculosis prevalence was higher in males (333; 95% CI: 233-433) and in the 35-54 year age group (355; 95% CI: 219-490)., Conclusion: The burden of tuberculosis remains high in Gambia but lower than earlier estimates of 490 per 100 000 population in 2010. Less than half of all cases would have been identified based on smear microscopy results alone. Successful control efforts will require interventions targeting men, increased access to radiography and more accurate, rapid diagnostic tests.
- Published
- 2016
- Full Text
- View/download PDF
5. A novel multiple-instance learning-based approach to computer-aided detection of tuberculosis on chest X-rays.
- Author
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Melendez J, van Ginneken B, Maduskar P, Philipsen RH, Reither K, Breuninger M, Adetifa IM, Maane R, Ayles H, and Sánchez CI
- Subjects
- Algorithms, Humans, Image Interpretation, Computer-Assisted methods, Radiography, Thoracic methods, Tuberculosis diagnostic imaging
- Abstract
To reach performance levels comparable to human experts, computer-aided detection (CAD) systems are typically optimized following a supervised learning approach that relies on large training databases comprising manually annotated lesions. However, manually outlining those lesions constitutes a difficult and time-consuming process that renders detailedly annotated data difficult to obtain. In this paper, we investigate an alternative approach, namely multiple-instance learning (MIL), that does not require detailed information for optimization. We have applied MIL to a CAD system for tuberculosis detection. Only the case condition (normal or abnormal) was required during training. Based upon the well-known miSVM technique, we propose an improved algorithm that overcomes miSVM's drawbacks related to positive instance underestimation and costly iteration. To show the advantages of our MIL-based approach as compared with a traditional supervised one, experiments with three X-ray databases were conducted. The area under the receiver operating characteristic curve was utilized as a performance measure. With the first database, for which training lesion annotations were available, our MIL-based method was comparable to the supervised system ( 0.86 versus 0.88 ). When evaluating the remaining databases, given their large difference with the previous image set, the most appealing strategy was to retrain the CAD systems. However, since only the case condition was available, only the MIL-based system could be retrained. This scenario, which is common in real-world applications, demonstrates the better adaptation capabilities of the proposed approach. After retraining, our MIL-based system significantly outperformed the supervised one ( 0.86 versus 0.79 and 0.91 versus 0.85 , and p=0.0002 , respectively).
- Published
- 2015
- Full Text
- View/download PDF
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