There is a great concern nowadays regarding alcohol consumption and drug
abuse, especially in young people. Analyzing the social environment where these
adolescents are immersed, as well as a series of measures determining the
alcohol abuse risk or personal situation and perception using a number of
questionnaires like AUDIT, FAS, KIDSCREEN, and others, it is possible to gain
insight into the current situation of a given individual regarding his/her
consumption behavior. But this analysis, in order to be achieved, requires the
use of tools that can ease the process of questionnaire creation, data
gathering, curation and representation, and later analysis and visualization to
the user. This research presents the design and construction of a web-based
platform able to facilitate each of the mentioned processes by integrating the
different phases into an intuitive system with a graphical user interface that
hides the complexity underlying each of the questionnaires and techniques used
and presenting the results in a flexible and visual way, avoiding any manual
handling of data during the process. Advantages of this approach are shown and
compared to the previous situation where some of the tasks were accomplished by
time consuming and error prone manipulations of data.

通过分析年轻人的社交环境、使用一系列问卷调查，如 AUDIT、FAS、KIDSCREEN 等，了解个体的饮酒行为，本研究设计并构建了一个基于网络的平台，通过集成不同阶段、直观的图形用户界面来简化问卷的创建、数据收集、整理和表达，以及后续的数据分析和可视化，从而避免了手动处理数据的繁琐步骤。与之前耗时且容易出错的数据操作相比，该方法具有一定的优势。

一个基于网络的工具，用于自动进行复杂医疗调查研究的数据收集、整理和可视化，包括社交网络分析

A Web-Based Tool for Automatic Data Collection, Curation, and  Visualization of Complex Healthcare Survey Studies including Social Network  Analysis

Most questionnaires offer ordered responses whose order is poorly studied via
belief functions. In this paper, we study the consequences of a frame of
discernment consisting of ordered elements on belief functions. This leads us
to redefine the power space and the union of ordered elements for the
disjunctive combination. We also study distances on ordered elements and their
use. In particular, from a membership function, we redefine the cardinality of
the intersection of ordered elements, considering them fuzzy.

本研究探讨了有序元素上信任函数的影响，并重新定义了幂空间和有序元素的联合。同时，对有序元素间的距离及其使用进行了研究，并从成员函数重新定义了有序元素的交集的基数。

有序分辨率框架上的信念函数

Belief functions on ordered frames of discernment

Undiagnosed diabetes is present in 21.4% of adults with diabetes. Diabetes
can remain asymptomatic and undetected due to limitations in screening rates.
To address this issue, questionnaires, such as the American Diabetes
Association (ADA) Risk test, have been recommended for use by physicians and
the public. Based on evidence that blood glucose concentration can affect
cardiac electrophysiology, we hypothesized that an artificial intelligence
(AI)-enhanced electrocardiogram (ECG) could identify adults with new-onset
diabetes. We trained a neural network to estimate HbA1c using a 12-lead ECG and
readily available demographics. We retrospectively assembled a dataset
comprised of patients with paired ECG and HbA1c data. The population of
patients who receive both an ECG and HbA1c may a biased sample of the complete
outpatient population, so we adjusted the importance placed on each patient to
generate a more representative pseudo-population. We found ECG-based assessment
outperforms the ADA Risk test, achieving a higher area under the curve (0.80
vs. 0.68) and positive predictive value (13% vs. 9%) -- 2.6 times the
prevalence of diabetes in the cohort. The AI-enhanced ECG significantly
outperforms electrophysiologist interpretation of the ECG, suggesting that the
task is beyond current clinical capabilities. Given the prevalence of ECGs in
clinics and via wearable devices, such a tool would make precise, automated
diabetes assessment widely accessible.

利用人工智能技术和心电图检测新发糖尿病的可行性，并表明它的测试表现超出了现有的预测工具。