Role of artificial intelligence in determining factors impacting patients’ refractive surgery decisions

Purpose: To create a predictive model using artificial intelligence (AI) and assess if available data from patients’ registration records can help in predicting definitive endpoints such as the probability of patients signing up for refractive surgery. Methods: This was a retrospective analysis. Electronic health records data of 423 patients presenting to the refractive surgery department were incorporated into models using multivariable logistic regression, decision trees classifier, and random forest (RF). Mean area under the receiver operating characteristic curve (ROC?AUC), sensitivity (Se), specificity (Sp), classification accuracy, precision, recall, and F1?score were calculated for each model to evaluate performance. Results: The RF classifier provided the best output among the various models, and the top variables identified in this study by the RF classifier excluding income were insurance, time spent in the clinic, age, occupation, residence, source of referral, and so on. About 93% of the cases that did undergo refractive surgery were correctly predicted as having undergone refractive surgery. The AI model achieved an ROC?AUC of 0.945 with an Se of 88% and Sp of 92.5%. Conclusion: This study demonstrated the importance of stratification and identifying various factors using an AI model which could impact patients’ decisions while selecting a refractive surgery. Eye centers can build specialized prediction profiles across disease categories and may allow for the identification of prospective obstacles in the patient’s decision?making process, as well as strategies for dealing with them.

Design of surgical procedures for patients with special protrusion with digital technology / 中华医学美学美容杂志

Objective:To analyze the symmetry of different reference planes in the surgical simulation design of patients with protrusive jaw deformity with high and low eyes.Methods:Fifteen patients with partial jaw deformity were selected from January 2019 to June 2020, including 3 males and 12 females, aged 18-26 years, with average 23.78 years. Inclusion criteria were that the patients, aged more than 18 years, were diagnosed as protrusive jaw deformity with maxillary occlusal plane tilt and high and low eyes by clinical and imaging analysis. Three different 3D reference plane systems were established by different modeling methods. The distance between the landmarks of soft and hard tissues and the median sagittal plane was measured. The symmetry of skull was qualitatively analyzed by mirror image technique. The difference of three reference planes in surgical simulation symmetry of patients with protrusion jaw and high and low eyes was evaluated by one-way ANOVA.Results:Qualitative analysis showed that in the three measurement planes, the symmetry of the third reference plane was the best, and the symmetry of the second and the first was poor. Quantitative analysis showed that in measurement index of hard tissue, there was statistical difference between the distance of each landmark in the reference plane established by Method 3 and Method 1, Method 2 [(1.65±1.19) mm; (3.37±1.58) mm; (3.26±2.36) mm, P<0.05], but there was no statistical difference between Method 1 and Method 2 (P > 0.05). The measurement result of soft tissue was consistent with that of hard tissue, and the distance of each landmark in Method 3 from the median sagittal plane was very small, and the mean error was less than 0.5 mm, which was consistent with the clinical results. Conclusions:Digital model surgery technology can assist orthognathic surgeons in the design and prediction of surgical scheme, especially for patients with special partial jaw deformity.

Prediction of dengue outbreaks in Kerala state using disease surveillance and meteorological data

Background: Dengue is one of the most serious and fast emerging tropical diseases. Its incidence of is influenced by many meteorological factors such as rain fall in mm, temperature, humidity etc. Information about these factors can be used to forecast the incidence of dengue fever cases in the next coming months.Methods: The current study was an analytical study using retrospective secondary data from Kerala state. The annual integrated disease surveillance reports of dengue fever cases. Rain fall data and mean monthly temperatures for a period of twelve years from 2006 to 2017 were used. Best fitted model was developed and accuracy of the prediction was tested. All analyses were performed in R software using the mgcv package and nlme package.Results: A total of 144 months study period from January 2006 to December 2017 was used for analysis. Five different models developed for prediction of dengue cases among them, best fitted model including optimal combination of meteorological variables and recent and long term transition of dengue was selected. Out of 84 months predictions in the training period, 68 months prediction was correctly negative, 5 months prediction was correctly positive, 2 months prediction was incorrectly negative and 9 months prediction was incorrectly positive.Conclusions: A better predictive generalized additive model can be developed using the optimal combination of meteorological predictors and dengue fever counts. It will enable the health care administrators to forecast future out breaks and to take better precautionary measures.

Prediction of maternal and child health care indicators in China based on GM(1,1) model / 中华疾病控制杂志

Objective To study the predictive effect of model ［GM(1,1)］ in China’s maternal and child health indicators, and to predict the future maternal and child health indicators in a short-term, and provide a scientific basis for the gradual improvement of maternal and child health care services in China. Methods The maternal mortality rate (MMR), neonatal mortality rate (NMR), infant mortality rate (IMR) and under-five mortality rate (U5MR) were collected from 2008 to 2017 in China. Models were established and MATLAB 2018b software was used for predictive analysis. Results The prediction models of maternal mortality rate, neonatal mortality rate, infant mortality rate and under-five mortality rate were as follows: x

Change and its clinical significance of T-lymphocyte subset in patients with hepatitis B virus-associated liver cancer / 国际检验医学杂志

Objective To assess the expression of T cell subset in patients with hepatitis B virus-associated primary liver cancer (HBV-PLC) and its influence on the clinical outcome.Methods 136 cases with PLC were selected, and divided into HBV-PLC group (78 cases) and non-HBV-PLC group (58 cases) according to HBV infection.The percentage of CD4+T cells, CD8+T cells and Treg cells in serum was tested by flow cytometry.After 6 months of follow-up, HBV-PLC patients were divided into death group and survival group.Binary logistic regression analysis was performed to explore the factor and degree affecting clinical outcome of HBVPLC patients.Results As compared with non-HBV-PLC group, dysregualted T cell subset was observed in the HBV-PLC group, percentage of CD4+T cells and Treg cells in HBV-PLC patients was higher (P＜0.05), while CD8+T cell percentage was decreased (P＜0.05).The percentage of CD4+T cells and Treg cells was higher in death group than survival group (P＜0.05), but CD8+T cell percentage was lower than that of survival group (P＜0.05).T-lymphocyte subset (CD4+T cells and Treg cells) was a strong risk factor for adverse clinical outcome of HBV-PLC (OR values were 3.765 and 2.238, respectively, P＜0.05), but CD8+T cell was a protective factor (OR value was-3.537, P＜0.05).Conclusion Obvious dysfunction of T cellular immune function exists in HBV-PLC patients, and T cell subset may be a predictive factor for clinical outcome of HBV-PLC patients.

Relaciones entre gratitud y felicidad en estudiantes universitarios de Lima Metropolitana / Relations Between Gratitude and Happiness in University Students of Metropolitan Lima

Se analiza la probable relación entre gratitud, medida por la Escala de gratitud desarrollada por Alarcón y la felicidad, medida por la Escala de felicidad de Lima, ambas desarrolladas por el mismo autor. El estudio es de tipo sustantivo, con un diseño transeccional causal predictivo en el que participaron 300 personas, 147 varones y 153 mujeres, con edades entre 20 y 30 años, que se encuentran estudiando en universidades públicas y privadas de Lima Metropolitana. Entre los principales resultados observamos que los factores de la gratitud, reciprocidad y obligación moral correlacionan positiva y significativamente con la felicidad (r = .294, p < .01; r = .293, p < .01), así como con los factores sentido positivo de la vida, satisfacción con la vida y realización personal de la Escala de felicidad. El agradecer el beneficio recibido y la satisfacción que esto conlleva tiende a estar relacionado con actitudes y experiencias positivas hacia la vida, satisfacción por lo que se ha alcanzado y la autosuficiencia y tranquilidad emocional. Cualidad sentimental se relaciona positiva y significativamente con la felicidad (r = .218, p < .05) y con satisfacción con la vida. Entre la gratitud y la felicidad no se observan diferencias estadísticamente significativas entre varones y mujeres. Para determinar cuál o cuáles de los factores de la gratitud predicen mejor la felicidad, se ha realizado un análisis de regresión múltiple, identificando que la variable reciprocidad explica el 8.7 % de la varianza total de la variable felicidad. En conclusión, se observa que gratitud y felicidad correlacionan positiva y significativamente (r=.318, p < .01).

Probable relationship between gratitude, as measured by the Scale developed by Alarcón gratitude and happiness, as measured by the Scale of Happiness Lima, is analyzed both developed by the same autor. The study is substantive in nature, with a predictive causal trans design in which 300 people, 147 males and 153 females, aged between 20 and 30 who are studying in public and private universities in Lima. Among the main results we note that the factors of gratitude, reciprocity and moral obligation positively and significantly correlated with happiness (r = .294, p < .01; r = .293, p < .01), as well as factors positive sense of life, life satisfaction and fulfillment of happiness scale. The benefit received thanks and satisfaction that entails tends to be related to positive experiences and attitudes towards life, satisfaction with what has been achieved and self-reliance and emotional tranquility. Emotional quality is positively and significantly associated with happiness (r = .218, p < .05) and satisfaction with life. Between gratitude and happiness no statistically significant differences between men and women are observed. To determine which of the factors best predict Gratitude happiness, there has been a multiple regression analysis, identifying varying reciprocity explains 8.7% of the total variance of the happiness variable. In conclusion, it appears that gratitude and happiness positively and significantly correlated (r = .318, p < .01).

Classificação de sinais de vozes saudáveis e patológicas por meio da combinação entre medidas da análise dinâmica não linear e codificação preditiva linear / Healthy and pathological voice assessment by means of nonlinear dynamic analysis measures and linear predictive coding

Análise acústica tem sido sugerida como uma ferramenta auxiliar não invasiva e de baixo custo ao diagnóstico de patologias laríngeas. Diversas são as técnicas empregadas, entre as quais técnicas baseadas no modelo linear de produção da fala e na análise dinâmica não linear de sinais de vozes. O primeiro método é baseado na Teoria fonte-filtro, em que a fonte é a laringe e o filtro é o trato vocal. Nesse modelo, os sons surdos são modelados por uma fonte de ruído aleatório e os sons sonoros por um trem de impulsos na frequência fundamental do locutor. Na abordagem não linear são considerados aspectos da voz humana, não explorados no modelo linear, tais como: variação temporal da forma do trato vocal, as ressonâncias associadas à sua fisiologia, as perdas devido ao atrito nas paredes internas do trato vocal, a radiação do som nos lábios, o acoplamento nasal e o comportamento dinâmico associado à vibração das pregas vocais. Neste trabalho são associadas as duas abordagens e avaliado o desempenho na classificação com as características, de forma individual, e a partir da combinação das mesmas. São empregadas oito medidas oriundas da análise dinâmica não linear (dimensão de correlação, quatro medidas de entropia, expoente de Hurst, maior expoente de Lyapunov e o primeiro mínimo da função de informação mútua), além de coeficientes LPC, obtidos a partir da análise preditiva linear. Os resultados sugerem a viabilidade da técnica empregada para a discriminação entre vozes saudáveis e patológicas em geral, como também entre vozes afetadas por patologias laríngeas distintas como edema, nódulos e paralisia nas pregas vocais.

Acoustic analysis has been suggested as a noninvasive aiding and low cost tool for laryngeal disease diagnosis. Several techniques are employed using either the linear model of speech production, or the nonlinear dynamic analysis of voice signals. The first method is based on source-filter theory, in which the source is the larynx and the filter is the vocal tract. In this model, the unvoiced sounds are modeled by a random noise source and the voiced ones by impulse train at the speaker fundamental frequency. In nonlinear approach, aspects of the human voice are considered, not explored in the linear model, such as temporal variation of the vocal tract shape, resonances associated with its physiology, losses due to friction in the vocal tract inner walls, sound radiation in the lips, nose coupling and dynamic behavior associated with vocal fold vibration. This work combines the two approaches and evaluates the performance in classifying the features individually, and from their combination. Eight measures are employed derived from the nonlinear dynamic analysis (correlation dimension, four entropy measures, Hurst exponent, the largest Lyapunov exponent and the first minimum of mutual information function), besides LPC coefficients obtained from linear predictive analysis. The results suggest the feasibility of the employed technique to discriminate between healthy and pathological voices in general, but also among specific laryngeal diseases as vocal fold edema, nodules and paralysis.