486 resultados para Specific recognition
Resumo:
BACKGROUND: Unnecessary intervention and overtreatment of indolent disease are common challenges in clinical management of prostate cancer. Improved tools to distinguish lethal from indolent disease are critical. METHODS: We performed a genome-wide survival analysis of cause-specific death in 24,023 prostate cancer patients (3,513 disease-specific deaths) from the PRACTICAL and BPC3 consortia. Top findings were assessed for replication in a Norwegian cohort (CONOR). RESULTS: We observed no significant association between genetic variants and prostate cancer survival. CONCLUSIONS: Common genetic variants with large impact on prostate cancer survival were not observed in this study. IMPACT: Future studies should be designed for identification of rare variants with large effect sizes or common variants with small effect sizes.
Resumo:
Localised prostate cancer is a heterogenous disease and a multi-modal approach is required to accurately diagnose and stage the disease. Whilst the use of magnetic resonance imaging (MRI) has become more common, small volume and multi-focal disease are oft en diffi cult to characterise. Prostate specifi c membrane antigen is a cell surface protein, which is expressed in nearly all prostate cancer cells. Its expression is signifi cantly higher in high grade prostate cancer cells. In this study, we compare multi-parametric magnetic resonance imaging and 68-Gallinium-PSMA PET with whole-mount pathology of the prostate to evaluate the applicability of multiparameteric (MP) MRI and 68Ga-PSMA PET in detecting and locating tumour foci in patients with localised prostate cancer.
Resumo:
The aim of this study was to identify and describe the types of errors in clinical reasoning that contribute to poor diagnostic performance at different levels of medical training and experience. Three cohorts of subjects, second- and fourth- (final) year medical students and a group of general practitioners, completed a set of clinical reasoning problems. The responses of those whose scores fell below the 25th centile were analysed to establish the stage of the clinical reasoning process - identification of relevant information, interpretation or hypothesis generation - at which most errors occurred and whether this was dependent on problem difficulty and level of medical experience. Results indicate that hypothesis errors decrease as expertise increases but that identification and interpretation errors increase. This may be due to inappropriate use of pattern recognition or to failure of the knowledge base. Furthermore, although hypothesis errors increased in line with problem difficulty, identification and interpretation errors decreased. A possible explanation is that as problem difficulty increases, subjects at all levels of expertise are less able to differentiate between relevant and irrelevant clinical features and so give equal consideration to all information contained within a case. It is concluded that the development of clinical reasoning in medical students throughout the course of their pre-clinical and clinical education may be enhanced by both an analysis of the clinical reasoning process and a specific focus on each of the stages at which errors commonly occur.
Resumo:
In this paper we focus on the challenging problem of place categorization and semantic mapping on a robot with-out environment-specific training. Motivated by their ongoing success in various visual recognition tasks, we build our system upon a state-of-the-art convolutional network. We overcome its closed-set limitations by complementing the network with a series of one-vs-all classifiers that can learn to recognize new semantic classes online. Prior domain knowledge is incorporated by embedding the classification system into a Bayesian filter framework that also ensures temporal coherence. We evaluate the classification accuracy of the system on a robot that maps a variety of places on our campus in real-time. We show how semantic information can boost robotic object detection performance and how the semantic map can be used to modulate the robot’s behaviour during navigation tasks. The system is made available to the community as a ROS module.
Resumo:
Issue addressed: Alcohol-related road crashes are a leading cause of the injury burden experienced by Indigenous Australians. Existing drink driving programs are primarily designed for the mainstream population. The ‘Hero to Healing’ program was specifically developed with Indigenous communities and is underpinned by the Community Reinforcement Approach (CRA). This paper reports on the formative evaluation of the program from delivery in two Far North Queensland communities. Methods: Focus groups and semistructured interviews were conducted with drink driver participants (n = 17) and other Elders and community members (n = 8) after each program. Qualitative content analysis was used to categorise the transcripts. Results: The CRA appealed to participants because of its flexible nature and encouragement of rearranging lifestyle factors, without specific focus on alcohol use. Participants readily identified with the social and peer-related risk and protective factors discussed. Cofacilitation of the program with Elders was identified as a key aspect of the program. More in-depth discussion about cannabis and driving, anger management skills and relationship issues are recommended. Conclusions: Participants’ recognition of content reinforced earlier project results, particularly the use of kinship pressure to motivate younger family members to drink drive. Study findings suggest that the principles of the CRA are useful; however, some amendments to the CRA components and program content were necessary. So what?: Treating drink driving in regional and remote Indigenous Australian communities as a community and social issue, rather than an individual phenomenon, is likely to lead to a reduction in the number of road-related injuries Indigenous people experience.