Early detection algorithm for alzheimer’s disease using autonomous learning

The current document describes the approach to a research problem that aims to generate an algorithm that allows detecting the probable appearance of Alzheimer’s disease in its first phase, using autonomous learning techniques or Machine Learning, more specifically KNN (K- nearest Neighbor) with which the best result was obtained. This development will be based on a complete information bank taken from ADNI (Alz- heimer’s Disease NeuroImaging Initiative), with all the necessary parameters to direct the inves- tigation to an algorithm that is as efficient as pos- sible, since it has biological, sociodemographic and medical history data, biological specimens, neural images, etc., and in this way the early de- tection of the aforementioned disease was con- figured. A complete guide to the process will be carried out to finally obtain the KNN algorithm whose efficiency is 99%, and then discuss the obtained results.

Resolvable Networks—A Graphical Tool for Representing and Solving SAT

In this paper, we introduce the notion of resolvable networks. A resolvable network is a digraph of subnetworks, where subnetworks may overlap, and the inner structure of subnetworks are not interesting from the viewpoint of the network. There are two special subnetworks, Source and Sink, with the following properties: there is no incoming edge to Source, and there is no outgoing edge from Sink. Any resolvable network can be represented by a satisfiability problem in Boolean logic (shortly, SAT problem), and any SAT problem can be represented by a resolvable network. Because of that, the resolution operation is valid also for resolvable networks. We can use resolution to find out or refine the inner structure of subnetworks. We give also a pessimistic and an optimistic interpretation of subnetworks. In the pessimistic case, we assume that inside a subnetwork, all communication possibilities are represented as part of the resolvable network. In the optimistic case, we assume that each subnetwork is strongly connected. We show that any SAT problem can be visualized using the pessimistic interpretation. We show that transitivity is very limited in the pessimistic interpretation, and in this case, transitivity corresponds to resolution of clauses. In the optimistic interpretation of subnetworks, we have transitivity without any further condition, but not all SAT problems can be represented in this case; however, any such network can be represented as a SAT problem. The newly introduced graphical concept allows to use terminology and tools from directed graphs in the field of SAT and also to give graphical representations of various concepts of satisfiability problems. A resolvable network is also a suitable data structure to study, for example, wireless sensor networks. The visualization power of resolvable networks is demonstrated on some pigeon hole SAT problems. Another important application field could be modeling the communication network of an information bank. Here, a subnetwork represents a dataset of a user which is secured by a proxy. Any communication should be done through the proxy, and this constraint can be checked using our model.

DATABASE PROTECTION BASED ON WEB APPLICATION FIREWALL

Web applications are increasingly being used in activities such as reading news, paying bills, and shopping online. As these services grow, you can see an increase in the number and extent of attacks on them, such as: theft of personal information, bank data and other cases of cybercrime. All of the above is a consequence of the openness of information in the database. Web application security is highly dependent on database security. Client request data is usually retrieved by a set of requests that request the application user. If the data entered by the user is not scanned very carefully, you can collect a whole host of types of attacks that use web applications to create security threats to the database. Unfortunately, due to time constraints, web application programmers usually focus on the functionality of web applications, but only few worry about security. This article provides methods for detecting anomalies using a database firewall. The methods of penetration and types of hacks are investigated. A database firewall is proposed that can block known and unknown attacks on Web applications. This software can work in various ways depending on the configuration. There are almost no false positives, and the overhead of performance is relatively small. The developed database firewall is designed to protect against attacks on web application databases. It works as a proxy, which means that requests for SQL expressions received from the client will first be sent to the developed firewall, rather than to the database server itself. The firewall analyzes the request: requests that are considered strange are blocked by the firewall and an empty result is returned to the client.

Relationship Between Levels of Digital Health Literacy Based on the Taiwan Digital Health Literacy Assessment and Accurate Assessment of Online Health Information: Cross-Sectional Questionnaire Study

Background The increasing amount of health information available on the internet makes it more important than ever to ensure that people can judge the accuracy of this information to prevent them from harm. It may be possible for platforms to set up protective mechanisms depending on the level of digital health literacy and thereby to decrease the possibility of harm by the misuse of health information. Objective This study aimed to create an instrument for digital health literacy assessment (DHLA) based on the eHealth Literacy Scale (eHEALS) to categorize participants by level of risk of misinterpreting health information into high-, medium-, and low-risk groups. Methods This study developed a DHLA and constructed an online health information bank with correct and incorrect answers. Receiver operating characteristic curve analysis was used to detect the cutoff value of DHLA, using 5 items randomly selected from the online health information bank, to classify users as being at low, medium, or high risk of misjudging health information. This provided information about the relationship between risk group for digital health literacy and accurate judgement of online health information. The study participants were Taiwanese residents aged 20 years and older. Snowball sampling was used, and internet questionnaires were anonymously completed by the participants. The reliability and validity of DHLA were examined. Logistic regression was used to analyze factors associated with risk groups from the DHLA. Results This study collected 1588 valid questionnaires. The online health information bank included 310 items of health information, which were classified as easy (147 items), moderate (122 items), or difficult (41 items) based on the difficulty of judging their accuracy. The internal consistency of DHLA was satisfactory (α=.87), and factor analysis of construct validity found three factors, accounting for 76.6% of the variance. The receiver operating characteristic curve analysis found 106 people at high risk, 1368 at medium risk, and 114 at low risk of misinterpreting health information. Of the original grouped cases, 89.6% were correctly classified after discriminate analysis. Logistic regression analysis showed that participants with a high risk of misjudging health information had a lower education level, lower income, and poorer health. They also rarely or never browsed the internet. These differences were statistically significant. Conclusions The DHLA score could distinguish those at low, medium, and high risk of misjudging health information on the internet. Health information platforms on the internet could consider incorporating DHLA to set up a mechanism to protect users from misusing health information and avoid harming their health.

Legal considerations about clinical records

The clinical record is a set of documents in which the care provided to the patient is accredited. It is the ideal mean by which the interventions of the health personnel, the patient’s authorizations and, in general, someone’s health condition gets established. On the one hand, it guarantees an information bank so patients may know the data related to their health, and on the other hand, it allows health personnel to accredit the service provided to the patient.

Relationship Between Levels of Digital Health Literacy Based on the Taiwan Digital Health Literacy Assessment and Accurate Assessment of Online Health Information: Cross-Sectional Questionnaire Study (Preprint)

BACKGROUND The increasing amount of health information available on the internet makes it more important than ever to ensure that people can judge the accuracy of this information to prevent them from harm. It may be possible for platforms to set up protective mechanisms depending on the level of digital health literacy and thereby to decrease the possibility of harm by the misuse of health information. OBJECTIVE This study aimed to create an instrument for digital health literacy assessment (DHLA) based on the eHealth Literacy Scale (eHEALS) to categorize participants by level of risk of misinterpreting health information into high-, medium-, and low-risk groups. METHODS This study developed a DHLA and constructed an online health information bank with correct and incorrect answers. Receiver operating characteristic curve analysis was used to detect the cutoff value of DHLA, using 5 items randomly selected from the online health information bank, to classify users as being at low, medium, or high risk of misjudging health information. This provided information about the relationship between risk group for digital health literacy and accurate judgement of online health information. The study participants were Taiwanese residents aged 20 years and older. Snowball sampling was used, and internet questionnaires were anonymously completed by the participants. The reliability and validity of DHLA were examined. Logistic regression was used to analyze factors associated with risk groups from the DHLA. RESULTS This study collected 1588 valid questionnaires. The online health information bank included 310 items of health information, which were classified as easy (147 items), moderate (122 items), or difficult (41 items) based on the difficulty of judging their accuracy. The internal consistency of DHLA was satisfactory (α=.87), and factor analysis of construct validity found three factors, accounting for 76.6% of the variance. The receiver operating characteristic curve analysis found 106 people at high risk, 1368 at medium risk, and 114 at low risk of misinterpreting health information. Of the original grouped cases, 89.6% were correctly classified after discriminate analysis. Logistic regression analysis showed that participants with a high risk of misjudging health information had a lower education level, lower income, and poorer health. They also rarely or never browsed the internet. These differences were statistically significant. CONCLUSIONS The DHLA score could distinguish those at low, medium, and high risk of misjudging health information on the internet. Health information platforms on the internet could consider incorporating DHLA to set up a mechanism to protect users from misusing health information and avoid harming their health.

Development of elements of a management system of preventive forecasting potential of complex technical systems

The article discusses the problems of forecasting technical and consumer characteristics at designing or modernization of complex technical systems. The model of the technique of complex technical system potential monitoring is proposed, it consists of two successive stages: analysis of technical level of the researched object relatively to its competitor and forecasting changes of consumer characteristics of the leading analogue for studied object using the moving average method. The methodology algorithm for monitoring of potential of a complex technical systems has been developed. The features of the developed methodology connected with obtaining of analytical data basing on which the enterprise becomes able to control the trends of complex technical systems modernization are indicated. Also the renewal of knowledge information bank will promote development of flexibility of small-scale production technological processes and adaptation to the factors of external competitive environment, adjusting itself to the needs of the current customer without extra human and financial resources.

Kajian Hukum Atas Hubungan Antara Nasabah Dan Bank Ditinjau Dari Undang-Undang Nomor 10 Tahun 1998 Perubahan Atas Undang-Undang Nomor 7 Tahun 1992 Tentang Perbankan

The relationship between banks and customers is based on the two most related elements, namely law and trust. A bank can only carry out activities and develop its bank, if the community "believes" to place its money, on banking products that exist in the bank. The higher the trust of the community, the higher the public's awareness to save money with the bank and to use other banking services. Public trust is the main key to the development or failure of a bank, in the sense that without the trust of the community, then a bank will not be able to carry out its business activities. For business people, banks are the main complement in carrying out daily activities, controlling the entry and exit of funds and achieving success, and are usually in the form of checking accounts. Based on this, the writer wants to examine more deeply the relationship between customers and banks regarding account information, bank rights and customer rights, and is associated with existing regulatory regulations.

Extraction and Analyze Text in Twitter using Naive Bayes Technique.

there are several topics and areas that are at an advanced stage of interest and research around the world because of their importance and usefulness to humanity, including the sentiment analysis. By studding of sentiment analysis (SA), one can learn about the mysterious things and different feelings of others. The purpose of all of this is to know the pros and cons about a product or anything else and correct the negatives in future that are found. In our research, we have benefited from social media sites, especially Twitter, in collecting data about the iPhone 11 product to see how satisfied customers are about this product. We collected a lot of different opinions using API and then transferred them to an information bank. In our research we used the famous Naive Bayes (NB) algorithm and had an active role in classifying reviews and sorting them and knowing the pros and cons, where we got good results compared to previous works which are as follows: precision 80, recall 83, f1 score 81, accuracy 80.25.