Objective To explore the feasibility of applying artificial intelligence (AI) technology in chromosomal aberration (CA) analysis for occupational health surveillance of radiation workers and in biological dose estimation during nuclear emergency responses. Methods Peripheral blood samples from healthy volunteers were irradiated in vitro with X-rays and cobalt-60 (⁶⁰Co) γ rays. Chromosome slides were prepared using an automated harvesting and dropping device. The data training and outcome evaluation of CA analysis was performed on the AI software using chromosome images from occupational medical examination of radiation workers from the current lab or chromosome slides from blood samples irradiated with X-rays. The trained AI software was then used to assist in CA analysis and biological dose estimation among occupational medical examination of radiation workers, with results compared with manual reading and actual exposure doses. Results The trained AI software achieved a CA recognition accuracy of 95.11%. In the occupational health examination of radiation workers, the positive CA detection rate using AI + manual review was 2.25% higher than that in manual reviewing alone. The errors in biological dose estimation for ⁶⁰Co γ rays and X-rays using AI + manual review analysis were 11.86% and 7.33%, respectively, both within the acceptable 20.00% error margin. Conclusion AI + manual review can be effectively applied in CA analysis for occupational health examination and biological dose estimation during nuclear emergencies, significantly improving analysis efficiency.

Objective:To investigate the modified application of orbicularis oculi muscle-levator aponeurosis composite tissue flap fixation technique (modified Park method) in double-eyelid surgery.Methods:From June 2019 to March 2021, 823 patients included 92 males and 731 females, aged from 18 to 45 years with mean (31.4±7.9) years, in which 142 patients with slightly ptosis were selected to receive the treatment in the Department of Plastic Surgery of the Affiliated Hospital of Nangjing University of TCM. The symmetry of bilateral double eyelids after operation was evaluated by the third party. The marginal reflex distance (MRD1) was measured before and 6 months after operation, and the difference between preoperative and postoperative MRD1 (ΔMRD1) was calculated. And the postoperative complications were counted. The patients were followed up from 6 to 12 months after surgery to evaluate the long-term results.Results:The patients were followed up for 4-22 months (mean 10 months) after operation. And the incisions of all the 823 cases had primary healling. Most patients had smooth upper eyelid crease, upturned lashes and dynamic fold. The skin tended to spread evenly without dimple. The symmetry evaluation by the third party showed that there were 764 patients with symmetry and basic symmetry after operation, the symmetry rate was 92.8%; 59 patients with asymmetry, the asymmetry rate was 7.2%. The data of MRD1 increased significantly 6 months after operation, from (3.25±0.72) mm to (3.64±0.61) mm, and the ΔMRD1 was (0.38±0.76) mm ( t=-20.41, P<0.05). The difference between the two groups was statistically significant. The double eyelid line became shallow in 8 cases and disappeared completely in 3 cases. The double eyelid curve of the patients was natural and smooth after the operation. And there was no obvious sunken scar and pretarsal fullness. Conclusions:The " modified Park technique" blepharoplasty can obtain a more firm, symmetrical and natural appearance. And the mild ptosis could be corrected by this method. The anatomical structure can be identified clearly, and the surgical results are highly repeatable. It is worth promoting.

Objective A deep learning-based method for evaluating the quality of pediatric pelvic X-ray images is proposed to construct a diagnostic model and verify its clinical feasibility.Methods Three thousand two hundred and forty-seven children with anteroposteric pelvic radiographs are retrospectively collected and randomly divided into training datasets,validation datasets and test datasets.Artificial intelligence model is conducted to evaluate the reliability of quality control model.Results The diagnostic accuracy,area under ROC curve,sensitivity and specificity of the model are 99.4%,0.993,98.6%and 100.0%,respectively.The 95%consistency limit of the pelvic tilt index of the model is-0.052-0.072.The 95%consistency threshold of pelvic rotation index is-0.088-0.055.Conclusion This is the first attempt to apply AI algorithm to the quality assessment of children's pelvic radiographs,and has significantly improved the diagnosis and treatment status of DDH in children.