ABSTRACT
Chinese herbal piece is an important component of the traditional Chinese medicine （TCM） system， and identifying their quality and grading can promote the development and utilization of Chinese herbal pieces. Utilizing deep learning for intelligent identification of Chinese herbal pieces can save time， effort， and cost， while also reasonably avoiding the constraints of human subjectivity， providing a guarantee for efficient identification of Chinese herbal pieces. In this study， a dataset containing 108 kinds of Chinese herbal pieces （14 058 images） was constructed，the basic YOLOv4 algorithm was employed to identify the 108 kinds of Chinese herbal pieces of our database The mean average precision （mAP） of the developed basic YOLOv4 model reached 85.3%. In addition， the receptive field block was introduced into the neck network of YOLOv4 algorithm， and the improved YOLOv4 algorithm was used to identify Chinese herbal pieces. The mAPof the improved YOLOv4 model achieved 88.7%， the average precision of 80 kinds of decoction pieces exceeded 80%， the average precision of 48 kinds of decoction pieces exceeded 90%. These results indicate that adding the receptive field module can help to some extent in the identification of Chinese herbal medicine pieces with different sizes and small volumes. Finally， the average precision of each kind of Chinese herbal medicine piece by the improved YOLOv4 model was further analyzed. Through in-depth analysis of the original images of Chinese herbal medicine pieces with low prediction average precision， it was clarified that the quantity and quality of original images of Chinese herbal medicine pieces are key to performing intelligent object detection. The improved YOLOv4 model constructed in this study can be used for the rapid identification of Chinese herbal pieces， and also provide reference guidance for the manual authentication of Chinese herbal medicine decoction pieces.
ABSTRACT
Objective To investigate the clinical significance and coagulation function changes in newborn hemolytic disease. Method The newborn hemolytic disease ( 60 cases, hemolytic disease group ), non-hemolytic hyperbilirubinemia (60 cases, non-hemolytic hyperbilirubinemia group) and normal newborn (60 cases,control group) were selected as the study subjects, the prothrombin time (PT) and activated partial thromboplastin time (APTT) were measured, and the blood platelet count at the same time was detected. Results PT and APTT in hemolytic disease group were higher than those in non-hemolytic hyperbilirubinemia group[(28.79 ?.21) s vs. (18.98?.41) s and (58.52?.13) s vs. (47.26?.81) s], and they were apparently higher than those in control group [(13.81 ?1.83) s and (38.10 ?3.00) s], the difference had statistic significance (P 0.05). Conclusions The newborn hemolytic disease has the bleeding tendency, and the bleeding tendency has no relationship with the quantity of the blood platelet, but relates to the extension of PT and APTT. The more serious the case is, the more obvious the PT and APTT rise. PT and APTT can be as the detection index and evaluating effect of the newborn hemolytic disease coagulation function.
ABSTRACT
ObjectiveTo investigate the change of D-dimer in haemolytic disease of newborn and its clinical significance. MethodsSixty cases with haemolytic disease of newborn were divided into nonserious group(34 cases) and serious group(26 cases) by the level of bilirubin, 40 cases of normal neonatus (control group) were also selected. The levels of D-dimer and fibrinogen(FIB) were measured and compared.ResultsThe level of D-dimer in serious group and non-serious group[ (9.29 ± 11.34), (0.84 ± 0.77 ) mg/L]was higher than that in control group [ (0.45 ± 0.06) mg/L](P ＜ 0.01 or ＜ 0.05 ),the level of D-dimer in serious group was higher than that in non-serious group (P＜ 0.01 ). There was no significant difference in the level of FIB among the three groups (P ＞ 0.05). ConclusionsThere is hypercoagulability in the serious haemolytic disease of newborn. It is valuable to detect plasma D-dimer density for serious haemolytic disease of judgement and treatment.