Objective To develop a deep learning system for CT images to assist in the diagnosis of thoracolumbar fractures and analyze the feasibility of its clinical application. Methods Collected from West China Hospital of Sichuan University from January 2019 to March 2020, a total of 1256 CT images of thoracolumbar fractures were annotated with a unified standard through the Imaging LabelImg system. All CT images were classified according to the AO Spine thoracolumbar spine injury classification. The deep learning system in diagnosing ABC fracture types was optimized using 1039 CT images for training and validation, of which 1004 were used as the training set and 35 as the validation set; the rest 217 CT images were used as the test set to compare the deep learning system with the clinician’s diagnosis. The deep learning system in subtyping A was optimized using 581 CT images for training and validation, of which 556 were used as the training set and 25 as the validation set; the rest 104 CT images were used as the test set to compare the deep learning system with the clinician’s diagnosis. Results The accuracy and Kappa coefficient of the deep learning system in diagnosing ABC fracture types were 89.4% and 0.849 (P<0.001), respectively. The accuracy and Kappa coefficient of subtyping A were 87.5% and 0.817 (P<0.001), respectively. Conclusions The classification accuracy of the deep learning system for thoracolumbar fractures is high. This approach can be used to assist in the intelligent diagnosis of CT images of thoracolumbar fractures and improve the current manual and complex diagnostic process.
Purpose To analyse the maculopathy in 597 eyes of 317 cases with diabetic retinopathy,and to explore the classification and visual prognosis. Methods Using fluorescein angiography to examine the extend of capillary leakage and foveal avascular zone as well as the extent of the capillary closure in macular area. Results ①Diabetic maculopathy was divided into 5 types,among 597 eyes,no leakage type 154 eyes (25.8%),focal edema type 188 eyes(31.5%),diffuse edema type (including cystoid edema)231 eyes(40.0%),ischemic type 12 eyes(2.0%) and proli ferative type was 4 eyes(0.7%).② There is close relationship between the classification and visual prognosis.such as when visual acuity was ge;0.5,no leakage type was 99.4%, focal edema type was 83.0%,diffuse edema type was 28.4%,ischemic type was 8.4%,and proliferative type was 0.5%.the visual acuity of cystoid edema was worse than diffuse edema only 20.3%.③The stage and visual prognosis:The higher the stage the worse the visual prognosis.if visual acuityge;0.5, 1 stage in 96.2% eyes,2 stage in 84.8%,3 stage in 53.2%,4 stage in 37.2%,5 stage in 12.5%. Conclusion Diabetic maculopathy is the main cause of visual impairment in diabetic retinopathy. Different type has different visual prognosis.macular edema and cystoid edema are the main factors to decrease visual acuity and could be treated by focal and grid laser photocoagulation to prevent visual loss. (Chin J Ocul Fundus Dis,2000,16:144-146)
ObjectiveTo investigate the methods and significances of the breast ultrasonographic breast imaging reporting and data system (BI-RADS) category 4 lesions divided into category 4a, 4b, and 4c, and to assess the risk of malig-nancy of lesions with BI-RADS category 4 in order to improve the accuracy of diagnosis. MethodsTwo hundred and eighty-eight breast lesions with BI-RADS category 4 confirmed by histopathology were collected. The ultrasonographic characteristics of benign and malignant lesions, containing the shape, aspect ration, margin, calcification, changes of the surrounding tissue, boundary, blood flow characteristics, internal echo, rear echo of the lesions, were comparatively anal-yzed, and the lesions with BI-RADS-US category 4 were divided into 4a, 4b, 4c according to these ultrasonographic charac-teristics and analyzed by statistics. ResultsThere were 192 malignant lesions and 96 benign lesions in the 288 breast lesions. There were statistical significances in the benign and malignant lesions with the shape, aspect ratio, margin, calci-fication, change of surrounding tissue, and boundary (P < 0.05), in other words, the proportion of these ultrasonographic characteristics were higher in the malignant lesions as compared with the benign lesions. But there were no significant differences of internal echo, rear echo, and blood flow characteristics between two lesions (P > 0.05). The positive predictive value of malignant tumor with BI-RADS category 4a, 4b, and 4c were 21.74%, 58.90%, and 91.78%, respectively, and there was significant difference (χ2=106.09, P=0.000). ConclusionsThe classification of breast lesions with BI-RADS category 4 is refined, it could more accurately assess the risk of benign and malignant breast masses. At the same time, it has an important clinical significance for diagnosis and treatment of benign and malignant breast masses.
Objective To study the clinical classification and etiologies of uveitis based on 1214 uveitis patients reffered to Zhongshan Ophthalmic Center. Methods A retrospective analysis was made on the patients with uveitis, coming from all over China between January 1996 and December 2001. All kinds of uveitis were classified according to the anatomical criteria and etiological criteria. The relevant data of these patients, such as the age at uveitis onset and sex were also analyzed. Results The total number of the patients is 1214 (male 698, female 516), with the average age at disease onset being 34.43. Anterior uveitis, the most common type, was seen in 546 cases, accounting for 44.98% of all the patients, followed in descending order by panuveitis (530 cases, 43.66%), intermediate uveitis(78 cases, 6.43%) and posterior uveitis(60 cases, 4.94%). Etiological factors and clinical entities were identified in 703 patients, accounting for 57.91% of all the patients, and the other 511 patients were idiopathic ones. The most common types of anterior uveitis were idiopathic uveitis(316 cases, 57.88%), followed by Fuchs syndrome(85 cases) and ankylosing spondylitis(45 cases). BehCcedil;et disease(218 cases, 41.13%) and Vogt-Koyanagi-Harada syndrome(196 cases, 36.98%) were the most common entities in panuveitis. Neither etiological factors nor clinical entities could be identified in the patients with intermediate uveitis and those with posterior uveitis. Conclusions Uveitis occurs mostly in young and middle-aged adults. In general, a predilection was seen in the male as compared with the female in the development of uveitis. Idiopathic anterior uveitis, BehCcedil;et disease and Vogt-Koyanagi-Harada syndrome are the most common entities of uveitis seen in China. Classification based on etiological and anatomical factors may provide a reasonable system for the study of uveitis. (Chin J Ocul Fundus Dis, 2002, 18: 253-255)
Objective To investigate the mass casualty triage system and its application, to provide evidence and advice for its future standardized use. Method Based on the principles and methods of systematic reviews, we searched MEDLINE (1950 to 2008), The Cochrane library (Issue 2, 2008) and CBM (from establishment to May 2008) to identify papers written in English of Chinese which described mass casualty triage systems or triage systems specific to the aftermath of earthquakes. We extracted information on name, grades, criteria, main characteristics and application of each triage system from the papers involving mass casualty triage systems. We also extracted information on setting, personnel performing the triage, grades, and characteristics from those papers describing any specific triage system for earthquake. We compared the colour of tags, codes and other materials used in different triage systems. Result We included 38 English and 6 Chinese papers. For mass casualty triage systems, we identified 7 primary triage methods with 4 grades.Three of these had relevant application reports. There were 6 secondary triage methods with 3-5 grades, and none had relevant application reports. Four tag methods were identified. Seven papers, 2 of which were published in China, reported specific secondary triage methods for earthquakes. Conclusion Based on the current evidence, there is no universally accepted mass casualty triage system with documented reliability and validity. No triage system has been developed specifically for the wounded in earthquakes. There are large differences between the triage methods for earthquake and other mass casualty incidents. Future research should focus on the development of a reliable and valid mass casualty triage system, aimed at maximizing the capacity for medical rescue.
Identification of molecular subtypes of malignant tumors plays a vital role in individualized diagnosis, personalized treatment, and prognosis prediction of cancer patients. The continuous improvement of comprehensive tumor genomics database and the ongoing breakthroughs in deep learning technology have driven further advancements in computer-aided tumor classification. Although the existing classification methods based on gene expression omnibus database take the complexity of cancer molecular classification into account, they ignore the internal correlation and synergism of genes. To solve this problem, we propose a multi-layer graph convolutional network model for breast cancer subtype classification combined with hierarchical attention network. This model constructs the graph embedding datasets of patients’ genes, and develops a new end-to-end multi-classification model, which can effectively recognize molecular subtypes of breast cancer. A large number of test data prove the good performance of this new model in the classification of breast cancer subtypes. Compared to the original graph convolutional neural networks and two mainstream graph neural network classification algorithms, the new model has remarkable advantages. The accuracy, weight-F1-score, weight-recall, and weight-precision of our model in seven-category classification has reached 0.851 7, 0.823 5, 0.851 7 and 0.793 6 respectively. In the four-category classification, the results are 0.928 5, 0.894 9, 0.928 5 and 0.865 0 respectively. In addition, compared with the latest breast cancer subtype classification algorithms, the method proposed in this paper also achieved the highest classification accuracy. In summary, the model proposed in this paper may serve as an auxiliary diagnostic technology, providing a reliable option for precise classification of breast cancer subtypes in the future and laying the theoretical foundation for computer-aided tumor classification.
Objective To assess the current status of medical waste management and classification disposal in hospitals across Hubei Province, providing a scientific basis for optimizing medical waste disposal strategies and promoting waste minimization, harmless treatment, and resource utilization. Methods A random sample survey was conducted on medical and health institutions in Hubei Province between January 8 and January 17, 2025. The self-made survey questionnaire was used to survey and analyze the medical waste management and classification disposal in medical and health institutions. Results A total of 257 medical and health institutions were surveyed. Among them, there were 93 tertiary hospitals (36.19%), 75 secondary hospitals (29.18%), 77 primary hospitals (29.96%), and 12 non-graded medical institutions (4.67%). The overall compliance rate for medical waste management and training exceeded 90%. In terms of medical waste supervision sections, compliance rates in primary hospitals and non-graded hospitals were 77.92% (60/77) and 58.33% (7/12), respectively. The compliance rate for medical waste classification and disposal was above 90%, with a 100% (221/221) compliance rate for the disposal of placentas from normal deliveries. However, the standardized disposal rates for “fetal tissues from pregnancies under 16 weeks or weighing less than 500 grams”, “amputation and other human tissues (or organs)” and “dead fetus” were 81.45% (180/221), 44.65% (96/215), and 79.64% (176/221), respectively. Additionally, 87.16% (224/257) of healthcare institutions classified single-use soft infusion bottles (bags) as recyclable waste, but significant variations were observed in the disposal of uncontaminated waste (e.g., empty disinfectant bottles, empty dialysis fluid barrels, oxygen humidifier bottles, and orthopedic casting materials). Furthermore, 99.61% (256/257) of hospitals provided protective equipment for medical waste handlers, 91.83% (236/257) conducted regular health examination to them, and 97.28% (250/257) had established needle stab reporting systems and related training programs. Conclusions Medical waste management and classification in hospitals across Hubei Province are largely standardized. However, the certain categories of medical waste still require stricter regulation and oversight.