1.Intelligent imaging technology applications in multidisciplinary hospitals.
Ke FAN ; Lei YANG ; Fei REN ; Xueyuan ZHANG ; Bo LIU ; Ze ZHAO ; Jianwen GU
Chinese Medical Journal 2024;137(24):3083-3092
With the rapid development of artificial intelligence technology, its applications in medical imaging have become increasingly extensive. This review aimed to analyze the current development status and future direction of intelligent imaging technology by investigating its application in various medical departments. To achieve this, we conducted a comprehensive search of various data sources up to 2024, including PubMed, Web of Science, and Google Scholar, based on the principle of comprehensive search. A total of 332 articles were screened, and after applying the inclusion and exclusion criteria, 56 articles were selected for this study. According to the findings, intelligent imaging technology exhibits robust image recognition capabilities, making it applicable across diverse medical imaging modalities within hospital departments. This technology offers an efficient solution for the analysis of various medical images by extracting and accurately identifying complex features. Consequently, it significantly aids in the detection and diagnosis of clinical diseases. Its high accuracy, sensitivity, and specificity render it an indispensable tool in clinical diagnostics and related tasks, thereby enhancing the overall quality of healthcare services. The application of intelligent imaging technology in healthcare significantly enhances the efficiency of clinical diagnostics, resulting in more accurate and timely patient assessments. This advanced technology offers a faster and more precise diagnostic approach, ultimately improving patient care and outcomes. This review analyzed the socioeconomic changes brought about by intelligent imaging technology to provide a more comprehensive evaluation. Also, we systematically analyzed the current shortcomings of intelligent imaging technology and its future development directions, to enable future research.
Humans
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Artificial Intelligence
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Diagnostic Imaging/methods*
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Hospitals
2.Mental Health Status and Its Influencing Factors among College Students during the Epidemic of Coronavirus Disease 2019:A Multi-center Cross-sectional Study.
Hao WANG ; Ming-Yu SI ; Xiao-You SU ; Yi-Man HUANG ; Wei-Jun XIAO ; Wen-Jun WANG ; Xiao-Fen GU ; Li MA ; Jing LI ; Shao-Kai ZHANG ; Ze-Fang REN ; You-Lin QIAO
Acta Academiae Medicinae Sinicae 2022;44(1):30-39
Objective To measure the prevalence of mental health symptoms and identify the associated factors among college students at the beginning of coronavirus disease 2019(COVID-19)outbreak in China. Methods We carried out a multi-center cross-sectional study via snowball sampling and convenience sampling of the college students in different areas of China.The rates of self-reported depression,anxiety,and stress and post-traumatic stress disorder(PTSD)were assessed via the 21-item Depression-Anxiety-Stress Scale(DASS-21)and the 6-item Impact of Event Scale-Revised(IES-6),respectively.Covariates included sociodemographic characteristics,health-related data,and information of the social environment.Data pertaining to mental health service seeking were also collected.Multivariate Logistic regression analyses were performed to identify the risk factors. Results A total of 3641 valid questionnaires were collected from college students.At the beginning of the COVID-19 outbreak,535(14.69%)students had negative emotions,among which 402(11.04%),381(10.49%),and 171(4.90%)students had the symptoms of depression,anxiety,and stress,respectively.Meanwhile,1245(34.19%)college students had PTSD.Among the risk factors identified,male gender was associated with a lower likelihood of reporting depression symptoms(AOR=0.755,P=0.037],and medical students were at higher risk of depression and stress symptoms than liberal arts students(AOR=1.497,P=0.003;AOR=1.494,P=0.045).Family support was associated with lower risks of negative emotions and PTSD in college students(AOR=0.918,P<0.001;AOR=0.913,P<0.001;AOR=0.899,P<0.001;AOR=0.971,P=0.021). Conclusions College students were more sensitive to public health emergencies,and the incidence of negative emotions and PTSD was significantly higher than that before the outbreak of COVID-19.More attention should be paid to female college students who were more likely to develop negative emotions.We should strengthen positive and proper propaganda via mass media and help college students understand the situation and impact of COVID-19.Furthermore,we should enhance family support for college students.The government and relevant agencies need to provide appropriate mental health services to the students under similar circumstances to avoid the deterioration of their mental well-being.
COVID-19/epidemiology*
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Cross-Sectional Studies
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Female
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Health Status
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Humans
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Male
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Students/psychology*
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Universities
3.Surgical options for benign prostatic hyperplasia: impact on sexual function and risk factors.
National Journal of Andrology 2011;17(9):837-841
Benign prostatic hyperplasia (BPH) is a common problem among elderly males. Surgical resection of the hyperplastic tissue to relieve urinary tract obstruction remains a major option for the treatment of BPH. Operations, whether open prostatectomy, transurethral resection of the prostate, or transurethral laser resection of the prostate, will inevitably affect the sexual function of the patient. With the increased attention to patients' quality of life, more and more importance is being attached to the changes in post-BPH sexual function. This review covers the sexual function changes induced by different surgical methods and assesses the possible risk factors of BPH surgery.
Erectile Dysfunction
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etiology
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Humans
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Male
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Prostatectomy
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adverse effects
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Prostatic Hyperplasia
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surgery
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Risk Assessment
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Risk Factors
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Transurethral Resection of Prostate
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adverse effects

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