METHODS: Accident-related autopsy reports were obtained from one of the largest hospital in Kuala Lumpur. These reports belong to nine different accident-related causes of death. Master feature vector was prepared by extracting features from the collected autopsy reports by using unigram with lexical categorization. This master feature vector was used to detect cause of death [according to internal classification of disease version 10 (ICD-10) classification system] through five automated feature selection schemes, proposed expert-driven approach, five subset sizes of features, and five machine learning classifiers. Model performance was evaluated using precisionM, recallM, F-measureM, accuracy, and area under ROC curve. Four baselines were used to compare the results with the proposed system.
RESULTS: Random forest and J48 decision models parameterized using expert-driven feature selection yielded the highest evaluation measure approaching (85% to 90%) for most metrics by using a feature subset size of 30. The proposed system also showed approximately 14% to 16% improvement in the overall accuracy compared with the existing techniques and four baselines.
CONCLUSION: The proposed system is feasible and practical to use for automatic classification of ICD-10-related cause of death from autopsy reports. The proposed system assists pathologists to accurately and rapidly determine underlying cause of death based on autopsy findings. Furthermore, the proposed expert-driven feature selection approach and the findings are generally applicable to other kinds of plaintext clinical reports.
OBJECTIVES: This research presents a novel homogeneous Pythagorean fuzzy framework for distributing the COVID-19 vaccine dose by integrating a new formulation of the PFWZIC and PFDOSM methods.
METHODS: The methodology is divided into two phases. Firstly, an augmented dataset was generated that included 300 recipients based on five COVID-19 vaccine distribution criteria (i.e., vaccine recipient memberships, chronic disease conditions, age, geographic location severity and disabilities). Then, a decision matrix was constructed on the basis of an intersection of the 'recipients list' and 'COVID-19 distribution criteria'. Then, the MCDM methods were integrated. An extended PFWZIC was developed, followed by the development of PFDOSM.
RESULTS: (1) PFWZIC effectively weighted the vaccine distribution criteria. (2) The PFDOSM-based group prioritisation was considered in the final distribution result. (3) The prioritisation ranks of the vaccine recipients were subject to a systematic ranking that is supported by high correlation results over nine scenarios of the changing criteria weights values.
CONCLUSION: The findings of this study are expected to ensuring equitable protection against COVID-19 and thus help accelerate vaccine progress worldwide.
BACKGROUND: The relationship between critical care nurses' decision-making and leadership styles in hospitals has been widely studied, but the influence of cognitive bias on decision-making and leadership styles in critical care environments remains poorly understood, particularly in Jordan.
DESIGN: Two-phase mixed methods sequential explanatory design and grounded theory.
SETTING: critical care unit, Prince Hamza Hospital, Jordan. Participant sampling: convenience sampling Phase 1 (quantitative, n = 96), purposive sampling Phase 2 (qualitative, n = 20).
METHODS: Pilot tested quantitative survey of 96 critical care nurses in 2012. Qualitative in-depth interviews, informed by quantitative results, with 20 critical care nurses in 2013. Descriptive and simple linear regression quantitative data analyses. Thematic (constant comparative) qualitative data analysis.
RESULTS: Quantitative - correlations found between rationality and cognitive bias, rationality and task-oriented leadership styles, cognitive bias and democratic communication styles and cognitive bias and task-oriented leadership styles. Qualitative - 'being competent', 'organizational structures', 'feeling self-confident' and 'being supported' in the work environment identified as key factors influencing critical care nurses' cognitive bias in decision-making and leadership styles. Two-way impact (strengthening and weakening) of cognitive bias in decision-making and leadership styles on critical care nurses' practice performance.
CONCLUSION: There is a need to heighten critical care nurses' consciousness of cognitive bias in decision-making and leadership styles and its impact and to develop organization-level strategies to increase non-biased decision-making.
METHODS: Ten focus group discussions were held with opinion leaders (chiefs, elders, assemblymen, leaders of women groups) and 16 in-depth interviews were conducted with healthcare workers (District Directors of Health, Medical Assistants in-charge of health centres, and district Public Health Nurses and Midwives). The interviews and discussions were audio recorded, transcribed into English and imported into NVivo 10 for content analysis.
RESULTS: As heads of the family, men control resources, consult soothsayers to determine the health seeking or treatment for pregnant women, and serve as the final authority on where and when pregnant women should seek medical care. Beyond that, they have no expectation of any further role during antenatal care and therefore find it unnecessary to attend clinics with their partners. There were conflicting views about whether men needed to provide any extra support to their pregnant partners within the home. Health workers generally agreed that men provided little or no support to their partners. Although health workers had facilitated the formation of father support groups, there was little evidence of any impact on antenatal support.
CONCLUSIONS: In patriarchal settings, the role of men can be complex and social and cultural traditions may conflict with public health recommendations. Initiatives to promote male involvement should focus on young men and use chiefs and opinion leaders as advocates to re-orient men towards more proactive involvement in ensuring the health of their partners.
METHODS: 28 experts from 11 countries reviewed the evidence and modified the statements using the Delphi method, with consensus level predefined as ≥80% of agreement on each statement. The Grading of Recommendation Assessment, Development and Evaluation (GRADE) approach was followed.
RESULTS: Consensus was reached in 26 statements. At an individual level, eradication of H. pylori reduces the risk of GC in asymptomatic subjects and is recommended unless there are competing considerations. In cohorts of vulnerable subjects (eg, first-degree relatives of patients with GC), a screen-and-treat strategy is also beneficial. H. pylori eradication in patients with early GC after curative endoscopic resection reduces the risk of metachronous cancer and calls for a re-examination on the hypothesis of 'the point of no return'. At the general population level, the strategy of screen-and-treat for H. pylori infection is most cost-effective in young adults in regions with a high incidence of GC and is recommended preferably before the development of atrophic gastritis and intestinal metaplasia. However, such a strategy may still be effective in people aged over 50, and may be integrated or included into national healthcare priorities, such as colorectal cancer screening programmes, to optimise the resources. Reliable locally effective regimens based on the principles of antibiotic stewardship are recommended. Subjects at higher risk of GC, such as those with advanced gastric atrophy or intestinal metaplasia, should receive surveillance endoscopy after eradication of H. pylori.
CONCLUSION: Evidence supports the proposal that eradication therapy should be offered to all individuals infected with H. pylori. Vulnerable subjects should be tested, and treated if the test is positive. Mass screening and eradication of H. pylori should be considered in populations at higher risk of GC.