1.Cost-minimization Analysis on 2 Drug Therapeutic Regimens for Children Pneumonia
Xuqiang HUANG ; Li DENG ; Huihong WEN ; Jialu YU ; Chang'An ZHAO ;
China Pharmacy 2005;0(20):-
0.05),but the total expenses and antibiotic cost of the medical treatment in group B were obviously lower than those in group A(P
2.A new strategy for the management of ascites in liver cirrhosis:A long-term albumin treatment
Lei WEN ; Huihong YU ; Xianlong LING
The Journal of Practical Medicine 2024;40(5):591-595
Ascites is the most frequent decompensating event of cirrhosis.At present,ascites recurs at a high rate due to lack of effective management strategy and is frequently complicated with spontaneous bacterial peritonitis,hepatorenal syndrome,and liver failure,which increase the fatality rate.Albumin treatment for hepatocirrhosic ascites has a long history,but it is limited as an acute or short-term treatment.In contrast,long-term albumin administration represents a completely different treatment paradigm.Results from several recent clinical studies indicate that long-term albumin treatment can be able to modify the disease courses of some decompensated cirrhosis when albumin is given at a sufficient dose for a sufficient time.In this review,we analyze the available data acquired from long-term albumin treatments,trying to establish a secure and effective management scheme involving maximal target popula-tion,albumin dose,administration time,and standards for albumin withdrawal,and thus provide references for the clinical practice.
3.Application of a wearable teleconsultation device in diagnosis of common skin diseases
Yue ZENG ; Huihong SHAO ; Shiwen LIN ; Rou WEN ; Xianbiao ZOU
Chinese Journal of Dermatology 2024;57(9):797-800
Objective:To preliminarily verify the feasibility of applying a wearable teleconsultation device in the diagnosis of common skin diseases.Methods:Totally, 600 outpatients with skin diseases were prospectively enrolled from the Department of Dermatology from November 1 to December 31 2023, and both on-site and remote diagnoses were performed. In the face-to-face clinic, there was one resident physician A and one chief physician B, while there was one resident physician C and one chief physician D in the remote consultation clinic. Using the diagnostic results of physician B in the face-to-face clinic as a reference, diagnostic agreement rates of physicians A, C, and D were calculated separately. Additionally, diagnostic results were compared between physician A and physician C, as well as between physician A and physician D. Statistical analysis was carried out using McNemar's test and Kappa consistency analysis.Results:Among the 600 patients with skin diseases, there were 285 males (47.50%) and 315 females (52.50%), and their age was 38.75 ± 21.12 years. The most common skin diseases were dermatitis and eczema (138 cases, 23.00%), followed by viral skin diseases (79 cases, 13.17%), urticaria (53 cases, 8.83%), hair diseases (53 cases, 8.83%), skin tumors (46 cases, 7.67%), fungal skin diseases (38 cases, 6.33%), etc. Compared with the physician B, the physician A made consistent diagnoses in 477 cases (79.5%) and inconsistent diagnoses in 123 cases (20.5%), the physician C made consistent diagnoses in 465 cases (77.5%) and inconsistent diagnoses in 135 cases (22.5%), and the physician D made consistent diagnoses in 568 cases (94.6%) and inconsistent diagnoses in 32 cases (5.33%). There was no significant difference in the diagnostic accuracy between the physician A and physician C ( P = 0.430), with a Kappa value of 0.852, indicating very strong consistency. The diagnostic accuracy of the physician D was significantly higher than that of the physician A ( P = 0.001), with a Kappa value of 0.274, indicating weak consistency. Conclusion:Chief dermatologists can provide medical guidance to resident physicians through a wearable teleconsultation system.
4.Application of deep learning in cancer prognosis prediction model.
Wen CHEN ; Xu WANG ; Huihong DUAN ; Xiaobing ZHANG ; Ting DONG ; Shengdong NIE
Journal of Biomedical Engineering 2020;37(5):918-929
In recent years, deep learning has provided a new method for cancer prognosis analysis. The literatures related to the application of deep learning in the prognosis of cancer are summarized and their advantages and disadvantages are analyzed, which can be provided for in-depth research. Based on this, this paper systematically reviewed the latest research progress of deep learning in the construction of cancer prognosis model, and made an analysis on the strengths and weaknesses of relevant methods. Firstly, the construction idea and performance evaluation index of deep learning cancer prognosis model were clarified. Secondly, the basic network structure was introduced, and the data type, data amount, and specific network structures and their merits and demerits were discussed. Then, the mainstream method of establishing deep learning cancer prognosis model was verified and the experimental results were analyzed. Finally, the challenges and future research directions in this field were summarized and expected. Compared with the previous models, the deep learning cancer prognosis model can better improve the prognosis prediction ability of cancer patients. In the future, we should continue to explore the research of deep learning in cancer recurrence rate, cancer treatment program and drug efficacy evaluation, and fully explore the application value and potential of deep learning in cancer prognosis model, so as to establish an efficient and accurate cancer prognosis model and realize the goal of precision medicine.
Deep Learning
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Humans
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Neoplasms
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Precision Medicine
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Prognosis