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Objective The diagnosis of nasal fractures poses challenges in forensic clinical evaluation.This study aims to develop and enhance an artificial intelligence-based model for nasal fracture recognition,evaluate its performance,and provide assistance and support for forensic clinical identification.Methods Multi-center nasal CT images were selected and screened according to the consensus standards set by Chinese experts in nasal CT examination and diagnosis.A recognition model was constructed,followed by external verification and evaluation.Additionally,the diagnostic capabilities of qualified appraisers/doctors with different professional titles(primary,intermediate,and senior)were compared with the performance of the intelligent recognition model.The accuracy,sensitivity,specificity),and negative predictive value(NP)of the intelligent recognition model were comprehensively evaluated.Results The intelligent recognition model exhibited high diagnostic efficiency and stability.It improved the diagnostic accuracy of radiologists and appraisers in detecting nasal fractures while effectively bridging the gap between inexperienced doctors/appraisers and experienced ones.Conclusion The intelligent recognition model for nasal fractures can assist appraisers in enhancing their ability to locate such fractures on CT images and improve work efficiency while enhancing appraisal opinions'accuracy and scientificity.
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Objective To investigate the recognition efficiency of AI model based on deep learning for cardiac conduction system(CCS).Methods HE staining sections of cardiac muscle and CCS of 17 cases of non-sudden death were selected,and the gold standard was unanimous recognition by 2 forensic pathologists with more than 20 years of CCS diagnosis experience.Inception V3 algorithm was used to establish AI model and complete CCS identification training and testing.Confusion matrix,accuracy,precision,recall,F1 score,ROC curve and AUC value were used to evaluate the effectiveness of AI model,and accuracy,sensitivity and specificity were used to evaluate the efficiency of manual independent and AI-assisted manual recognition for CCS.Results The accuracy of AI model was 87.3%,the precision was 91.9%,the recall was 81.9%,the F1 score was 86.6%,and the AUC value was 95.3%.The accuracy of AI model was higher than that of senior forensic pathologists.There was no statistical significance in the accuracy of AI-assisted senior forensic pathologists in identifying CCS compared with manual independent detection(P>0.05),while the accuracy of AI-assisted intermediate and junior forensic pathologists in identifying CCS was increased by 8%and 14.33%,respectively,with statistical significance(P<0.05).The accuracy rate of AI-assisted junior forensic pathologists to identify CCS was higher than that of intermediate forensic pathologists in self-diagnosis.Conclusion The AI model could be used for the automatic recognition of CCS,and could improve the diagnostic efficiency of CCS and narrow the gap between the forensic pathologists with low experience and that with high experience.
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Objective To conduct a comprehensive visual analysis of the application of Artificial Intelligence(AI)in forensic medicine using bibliometric tools so as to create knowledge maps of cooperation network,research hotspots,important findings,and potential future trends in this field.Methods The Web of Science(WoSCC)was utilized as the primary data source,search formula incorporating AI and forensic medicine as core subject words was constructed,resulting in a dataset comprising 2 287 literature records.Vosviewer,Citespace,and Bibliometrix were employed for analyzing various aspects such as cooperation network,keyword co-occurrence networks,clustering dynamics,clusters,centrality degree and thematic strategic coordinate charts.These analyses facilitated the creation of corresponding visual maps.Results The collaboration among authors still requires further strengthening;however significant groups have emerged among institutions and countries.Research hotspots and important findings predominantly revolve around algorithmic applications.Furthermore,"identification"related research appears to become a prominent future research trend.Conclusion By employing bibliometric analysis techniques on the application of artificial intelligence in forensic medicine domain,this study successfully elucidats cooperation networks,research hotspots,important findings,future research directions,and provides objective support through empirical evidence for related studies.
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Tissue analysis by Fourier transform infrared (FTIR) imaging can determine the biodistribution of molecules,without pre-analytical modification. We aimed to study the infrared spectroscopic changes of a-helical proteinsat post-traumatic epileptic (PTE) foci by FTIR. FITR mapping was applied to detect a-helical proteins in ratbrain tissue samples with post-traumatic epilepsy. Histological examination of brain sections showed that therat model of PTE was successfully established. At the PTE foci, high a-helical absorption regions wereevident, where the color difference and absorption were significantly different from those in the low-absorptionregions. This provided a distinctive and characteristic pattern at the site of lesions. The use of FTIR imagingmeans that it is possible to measure the molecular structural changes resulting from PTE pathologies in tissues,providing a novel adjunct to conventional pathological diagnostic techniques.
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The article is study about range of motion on lower extremities on Guides to the Evaluation of Permanent Impairment. We reviewed the latest range of motion concept about lower extremities evaluation of GEPI. We also introduced measurement and procedure of range of motion evaluation. To provide advice for construction of disability evaluation system in China.
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Objective The article is to study on the detection of α-helix proteins in post-traumatic epileptogenic focus by FTIR-mapping. Methods Fourier transform infrared spectroscopy-mapping were applied to identifying α-helix by point-by-point scanning in post-traumatic epileptogenic focus sections and to develop FTIR-mapping profiles. Result The high absorbance of α-helix is accord with post-traumatic epilepsy, there are some significant differences between high absorbance and low absorbance. Conclusion α-helix proteins are distributed in post-traumatic epileptogenic focus widely, thus α-helix protein are involved in post-traumatic epilepsy.
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The article is study about principle of lower extremities on Guides to the Evaluation of Permanent Impairment. We reviewed the latest concept in lower extremities evaluation of GEPI, such as regional impairment, diagnosis based impairment and grade modifier. We also introduced maximum medical improvement and conversion from lower extremities impairment to whole person impairment. To provide advice for construction of disability evaluation system in China.
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The article is comparative study about spine and extremities on clause for the identification of the body injured and The classification of the body impairment. We reviewed the terms and provisions about spine and extremities as follows, amputation impairment, function impairment, and amputation impairment combined function impairment. This paper provides a comprehensive access and analysisofthe similarities and differences between the two standards.
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Objective To investigate the relationship between K+ concentration in rabbit vitreous humor and postmortem interval (PMI) under different ambient temperature. Methods Rabbit corpses were stored at 5℃ , 15℃ , 25℃ , and 35℃ after execution, and 80~100μL vitreous humor was extracted from each eye of the rabbit in turn every 12 hours. The concentrations of K+ were examined by Modular DPPI automatic biochemistry analyzer. The Interpolation Functions were used to analyze the statistical relationship between PMI and K+ concentration under different temperature. Results In each animal group, K+ concentration increased with PMI. Equation was obtained after interpolation analysis on range of temperature 5℃ ~30℃ . The three-variable quintic surface equation was f(x,y)=-1.998e14+1.345e12x+5.902e13y+0.005585x2-4.509e11xy-3.876e12y2-0.0002868x3+0.003545x2y+4.406e10xy2-1.746e10y3+2.669e-6x4-1.568e-5x3y-0.0001771x2y2-1.64e9xy3+6.669e9y4-8.672e-9x5+4.467e-8x4y+2.354e-7x3y2+2.459e-6x2y3+2.05e7xy4-1.214e8y5(R2=0.9956), x stands for temperature, y stands for K+ concentration, f(x,y) stands for PMI. Conclusion The rule of K+ concentration changes at ambient temperature complied with three-variable quintic surface equation distribution. Measurement of interpolation function may be used for PMI estimation at different ambient temperature.
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Objective It aims to investigate the relationships among the categories of Comprehensive Version for Stroke as described in the International Classiifcation of Functioning, Disability and Health (ICF) Core Set, and to provide new supports for Judicial Appraisal of functioning in stroke by ICF functioning mapping.Methods The variables of 59 categories of ICF assessment scale and the samples of 106 persons’ are selected and used in the least absolute shrinkage and selection operator (LASSO) for mining dependencies among those variables. The graphical modeling and analyzing with the software Gephi provides a visual map of the correlations among those classiifcations. Results 59 interconnected categories which organized into the functioning mapping. b340, b735, b175 and b152 are centrally positioned categories because of their high correlation.Conclusion Functioning mapping by graphical modeling can reveal complex relational structures embedded in functioning classiifcations, which provides the support for using ICF to appraisal stroke.
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Objective To investigate the relationship between Ct value of mice liver and postmortem interval (PMI) under various ambient temperatures. Methods mice were stored at 10℃, 15℃, 20℃, 25℃ and 30℃ after execution, and total RNA was extracted from mice liver every 6 hours (PMI 6h to 72h). The levels of 18s rRNA were examined using real-time PCR. The results were expressed by cycle threshold (Ct) value to explore relationship between PMI and Ct value, and the interpolation functions were established to estimate PMI. Results In each group, Ct value increased with PMI increased. Surface equation was obtained after interpolation analysis on temperature range 10℃~30℃. The three-variable quintic surface equation was f(x, y)=-426.9+30.82x+44.48y-1.297x2-1.837xy-1.388y2+0.034 38x3+0.038 17x2y+0.038 67xy2+0.028 77y3-0.000 612 9x4-3.897e-7x3y-0.001 223x2y2+0.000 256 6xy3-0.000 537 4y4+3.606e-6x5-2.846e-6x4y+1.009e-5x3y2-3.439e-6x2y3-2.556e-7xy4+2.664e-6y5(r2=0.999 4). Conclusion The rule of Ct value changes at ambient temperature complied with three-variable quintic surface equation distribution. Measurement of interpolation function may be used for PMI estimation at ambient temperature.
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The aim of the present study was to assess whether Fourier transform infrared spectrometry (FTIR) micro-spectroscopy could produce distinct spectral information on protein of old myocardial infarction (OMI) and to set them as molecular markers to diagnose atypical OMI. Paraffin-embedded heart samples were derived from victims dying of OMI. In combination with histological stain, FTIR and infrared micro-spectroscopy, the characteristics of OMI were analyzed morphologically and molecularly. The most relevant bands identified were the amide A, B, I and, II showing crucial spectral differences between apparent normal region and OMI region, including the peak position blue shift and the increased intensity of OMI, moreover relative increase in alpha-helix and decrease in beta-sheet of protein secondary structures in OMI. Comparing to single spectral band, the I1650/I1550 ratio was increased and rationally used as a molecular marker for diagnosing OMI. These novel preliminary findings supported further exploration of FTIR molecular profiling in clinical or forensic study, and were in accordance with histopathology.