RESUMO
BACKGROUND: Double reading (DR) in screening mammography increases cancer detection and lowers recall rates, but has sustainability challenges due to workforce shortages. Artificial intelligence (AI) as an independent reader (IR) in DR may provide a cost-effective solution with the potential to improve screening performance. Evidence for AI to generalise across different patient populations, screening programmes and equipment vendors, however, is still lacking. METHODS: This retrospective study simulated DR with AI as an IR, using data representative of real-world deployments (275,900 cases, 177,882 participants) from four mammography equipment vendors, seven screening sites, and two countries. Non-inferiority and superiority were assessed for relevant screening metrics. RESULTS: DR with AI, compared with human DR, showed at least non-inferior recall rate, cancer detection rate, sensitivity, specificity and positive predictive value (PPV) for each mammography vendor and site, and superior recall rate, specificity, and PPV for some. The simulation indicates that using AI would have increased arbitration rate (3.3% to 12.3%), but could have reduced human workload by 30.0% to 44.8%. CONCLUSIONS: AI has potential as an IR in the DR workflow across different screening programmes, mammography equipment and geographies, substantially reducing human reader workload while maintaining or improving standard of care. TRIAL REGISTRATION: ISRCTN18056078 (20/03/2019; retrospectively registered).
Assuntos
Neoplasias da Mama , Humanos , Feminino , Neoplasias da Mama/diagnóstico por imagem , Mamografia , Inteligência Artificial , Estudos Retrospectivos , Detecção Precoce de Câncer , Programas de RastreamentoRESUMO
There are numerous better applications of fibre reinforced polymer composites today, when compared with metals and alloys. Many studies have been conducted to further improve the inherent mechanical and thermal properties of the composite materials, especially with sustainable, environmental friendly, recyclable and biodegradable reinforcements. Consequently, in this current study, the composites were prepared by combining bio solid waste (date seed filler) and vinyl ester to enhance the properties of polymer composites. The date seed filler reinforced vinyl ester (DSF-VE) composites were prepared by using conventional compression moulding technique with varying fillers loadings from 5% to 50%. The mechanical (tensile, flexural, impact and hardness), water absorption and thermal (heat deflection temperature and thermo-gravimetric analysis) properties of the DSF-VE composites were experimentally evaluated. Scanning electron microscopic analysis was carried out to analyse the surface characteristics and fractured surface of the DSF-VE composites. It was evident from the results obtained that 30 wt% of the DSF-VE composites exhibited the highest mechanical properties: impact, tensile, hardness and flexural of 17.03 KJ/m2, 40.3 MPa, 51 and 149 MPa, respectively, among the fabricated composites. Similarly, the heat deflection temperatures of DSF-VE composites increased by 58.49%, when compared with the neat, pure vinyl ester resin. The thermo-gravimetric analysis showed that the natural filler-based (DSF-VE) composites possessed thermal stability up to 400.2 °C, which was within the polymerisation process temperature. Furthermore, the DSF-VE composites have been successfully utilized for various potential applications, such as fabrication of a table fan blade, an engine guard for two-wheelers and self-motor guard for four wheelers.