Academic Dissertations as Topic ; Epidemiologic Methods ; Forecasting

It is important to forecast incidence rates of infectious disease for the development of a better program on its prevention and control. Since the incidence rate of infectious disease is influenced by multiple factors, and the action mechanisms of these factors are usually unable to be described with accurate mathematical linguistic forms, the radial basis function (RBF) neural network is introduced to solve the nonlinear approximation issues and to predict incidence rates of infectious disease. The forecasting model is constructed under data from hepatitis B monthly incidence rate reports from 1991-2002. After learning and training on the basic concepts of the network, simulation experiments are completed, and then the incidence rates from Jan. 2003-Jun. 2003 forecasted by the established model. Through comparing with the actual incidence rate, the reliability of the model is evaluated. When comparing with ARIMA model, RBF network model seems to be more effective and feasible for predicting the incidence rates of infectious disease, observed in the short term.
Communicable Diseases ; Forecasting ; methods ; Humans ; Models, Theoretical

OBJECTIVETo explore the application of the gray series model GM (1, 1) in predicting trends in the incidence of pneumoconiosis and evaluate its degree of predicted precision.

METHODSAnalyzing the incidence of pneumoconiosis in this region from 2009 to 2013, and predicting the incidence of pneumoconiosis of the area in 2014-2016 by establishing GM (1, 1) according to the gray system theory.

RESULTSUsing occupational pneumoconiosis population data from 2009 to 2013, to establish GM (1, 1) model: yt = 1396.89e(0.12(t-1)), α = -0.12, µ = 147.2. The pneumoconiosis in 2014, 2015, 2016 were predicted respectively 51, 47, 43 cases based on the GM (1, 1) model, and C value of model is 0.15, P value is 1, all of them meet the requirements of model predictions. It shows the cases of pneumoconiosis are rising significantly.

CONCLUSIONGM (1, 1) model can be used to predict the recent trend in the incidence of pneumoconiosis.

Forecasting ; methods ; Humans ; Incidence ; Models, Theoretical ; Pneumoconiosis ; epidemiology

A dynamic multiway principle component analysis for on-line batch process monitoring and fault detection was proposed. It integrates the time-lagged windows of process dynamic behavior with the multiway principle component analysis (MPCA). Using multi-model instead of single model, the dynamic MPCA approach emphasizes particularly on-line process performance monitoring and fault defecting. On-line process monitoring of cephalosporin C fermentation was studied, the results demonstrate that the dynamic MPCA method is able to efficiently monitor performance of the fermentation process and exactly detect faults which results in extraordinary behavior of processes.
Cephalosporins ; biosynthesis ; Fermentation ; Forecasting ; Nonlinear Dynamics ; Principal Component Analysis ; methods

Forecasting ; History, Ancient ; Humans ; Medicine, Chinese Traditional ; methods ; trends

Head and neck cancers become a severe threat to human's health nowadays and represent the sixth most common cancer worldwide. Surgery remains the first-line choice for head and neck cancer patients. Limited resectable tissue mass and complicated anatomy structures in the head and neck region put the surgeons in a dilemma between the extensive resection and a better quality of life for the patients. Early diagnosis and treatment of the pre-malignancies, as well as real-time in vivo detection of surgical margins during en bloc resection, could be leveraged to minimize the resection of normal tissues. With the understanding of the head and neck oncology, recent advances in optical hardware and reagents have provided unique opportunities for real-time pre-malignancies and cancer imaging in the clinic or operating room. Optical imaging in the head and neck has been reported using autofluorescence imaging, targeted fluorescence imaging, high-resolution microendoscopy, narrow band imaging and the Raman spectroscopy. In this study, we reviewed the basic theories and clinical applications of optical imaging for the diagnosis and treatment in the field of head and neck oncology with the goal of identifying limitations and facilitating future advancements in the field.
Forecasting ; Head and Neck Neoplasms ; diagnostic imaging ; Humans ; Optical Imaging ; methods

Child ; Cytogenetic Analysis ; Forecasting ; Humans ; Immunohistochemistry ; Pathology, Clinical ; methods ; trends ; Pediatrics ; methods ; trends

Traditional Chinese medicine clinical pharmacy is the contact theory of traditional Chinese medicine and herbal application on the bridge, this paper systematically reviews the clinical pharmacy of traditional Chinese medicine the history, current situation of clinical pharmacy to conduct a comprehensive review, put forward the development of Chinese clinical pharmacy path, in order to strengthen the traditional Chinese medicine clinical pharmacy discipline construction and research.
Forecasting ; Humans ; Medicine, Chinese Traditional ; methods ; trends ; Pharmacists ; Pharmacy Service, Hospital ; methods ; trends ; Professional Role

Therapeutic drug monitoring (TDM) is the clinical practice of measuring specific drugs at designated intervals to maintain a constant concentration in a patient's bloodstream, thereby optimizing individual dosage regimens. It is unnecessary to employ TDM for the majority of medications, and it is used mainly for monitoring drugs with narrow therapeutic ranges, drugs with marked pharmacokinetic variability, medications for which target concentrations are difficult to monitor, and drugs known to cause therapeutic and adverse effects. The process of TDM is predicated on the assumption that there is a definable relationship between dose and plasma or blood drug concentration, and between concentration and therapeutic effects. TDM begins when the drug is first prescribed, and involves determining an initial dosage regimen appropriate for the clinical condition and such patient characteristics as age, weight, organ function, and concomitant drug therapy. When interpreting concentration measurements, factors that need to be considered include the sampling time in relation to drug dose, dosage history, patient response, and the desired medicinal targets. The goal of TDM is to use appropriate concentrations of difficult-to-manage medications to optimize clinical outcomes in patients in various clinical situations.
Algorithms ; Dose-Response Relationship, Drug ; Drug Monitoring/*methods/trends ; Forecasting ; Humans ; Patient Compliance ; Pharmacokinetics

OBJECTIVEIt is necessary to compensate the system latencies in real-time tumor-tracking radiotherapy by prediction. However, due to the irregularities of respiratory motions, the results obtained with traditional methods were not acceptable. The purpose of this study is to evaluate the value of nonparametric regression model in respiratory motion prediction.

METHODSThe data of respiratory trajectory of 11 volunteers were obtained and predicted based on nonparametric regression method. The results were compared with those of autoregressive model and back propagation neural network. An improved method was proposed to deal with the abnormal state in respiration. We combined the prediction method with the tracking system to test its performance in practical application.

RESULTSThe results indicated that the proposed method could predict the motion accurately in real-time for different latencies. This method decreased the error of the abnormal state substantially and also allowed effective prediction of respiration motion when combined with the tracking system.

CONCLUSIONThe nonparametric regression model can predict the respiratory motion accurately in real-time and therefore meets the requirement of real-time tumor-tracking radiotherapy.

Forecasting ; Humans ; Models, Theoretical ; Movement ; Neoplasms ; radiotherapy ; Radiotherapy, Computer-Assisted ; methods ; Regression Analysis ; Respiration