Causal factors identification and dynamics simulation of major road traffic accidents from China's evidence: A high-order mixed-method design.

Mitigating the injury and severity of road traffic accidents has become a crucial objective in global road safety efforts. Major road traffic accidents (MRTAs) pose significant challenges due to their high hazard and severe consequences. Despite their widespread impact, the complex causation mechanisms behind MRTAs have not been thoroughly and systematically investigated, which hinders the development of effective control strategies and policies.

Delta Radiomics Based on MRI for Predicting Axillary Lymph Node Pathologic Complete Response After Neoadjuvant Chemotherapy in Breast Cancer Patients.

Purpose: To develop and test a radiomics nomogram based on magnetic resonance imaging (MRI) and clinicopathological factors for predicting the axillary pathologic complete response (apCR) to neoadjuvant chemotherapy (NAC) in breast cancer patients with axillary lymph node (ALN) metastases.

Materials And Methods: A total of 319 patients who underwent MRI examination and received NAC treatment were enrolled from two centers, and the presence of ALN metastasis was confirmed by biopsy pathology before NAC. The radiomics features were extracted from regions of interest of ALNs before (pre-radiomics) and after (post-radiomics) NAC.

The hybrid systems method integrating STAMP and HFACS for the causal analysis of the road traffic accident.

The role of traditional analysis methods in improving complex socio-technical system safety has reached a ceiling, and thus systems theory has been utilised to support the investigations and countermeasures for road traffic accidents. As two widely applied systems accident analysis models, STAMP (systems theoretic accident model and process) and HFACS (human factors analysis and classification system) have their own advantages in accident analysis and safety improvement. Therefore, this study develops a new hybrid systems method integrating STAMP and HFACS for road traffic accident (SH-RTA), which can adopt HFACS to enhance the identification and analysis ability of STAMP for human factors and employ control concepts and elements of STAMP to cement the characteristic of HFACS.