Сashless payment sofware module for self-service systems

With the development of technology and computerization, humanity is entering a new stage of modernization of society every year. This happens in all spheres of life. From medicine and the creation of new medical computer devices to everyday activities, such as paying for groceries. Contactless payments are largely how they sound - a way to pay for goods or services, without other physical needs to go through your automation or transfer it to the person. If you've even seen a passerby press his phone at the checkout to pay late, you've witnessed this technology. Describes the creation of a cashless payment module. Software and hardware has been created that can function autonomously and uninterruptedly. The module has a compact size, placed in places for easy payment. The module is of medium price shade in order to successfully enter the product market.

Skin Cancer Detection and Classification using KNN Technique

Skin cancer is a major health issue worldwide. Skin cancer detection at an early stage is key for an efficient treatment. Lately, it is popular that, deadly form of skin cancer among the other types of skin cancer is melanoma because it's much more likely to spread to other parts of the body if not identified and treated early. The advanced medical computer vision or medical image processing take part in increasingly significant role in clinical detection of different diseases. Such method provides an automatic image analysis device for an accurate and fast evaluation of the sore. The steps involved in this project are collecting skin cancer images from PH2 database, preprocessing, segmentation using thresholding, feature extraction and then classification using K-Nearest Neighbor technique (KNN). The results show that the achieved classification accuracy is 92.7%, Sensitivity 100% and 84.44% Specificity.

USE OF SECTRA VIRTUAL DISSECTION TABLE IN THE EDUCATIONAL PROCESS

The article features the research of the effectiveness of using the virtual dissection table in medical higher educational institutions. The theoretical and methodological foundations of the use of the virtual dissection table in the training of future medical specialists are determined, practical aspects are described. Laboratory works have been created on the use of the virtual dissection table in teaching theoretical and clinical disciplines in medical higher education institutions. The authors considered the formation of the following components of students’ experimental competence through the use of Sectra Virtual Dissection Table during the lessons: cognitive-intellectual, diagnostic, prognostic, information, analytical and research. The cross-curricular links between the disciplines "Human Anatomy" and "Medical and Biological Physics" in view of the formation of the aforementioned experimental competences are considered. The algorithm for work with the muscular system in the Human Anatomy Atlas program on the Sectra Table F18 Virtual Dissection Table is described in detail. The authors showed the capabilities of the Sectra Virtual Dissection Table: viewing realistic human anatomy; simulation of the human body in combination with 3D touch control when viewing, panning, rotating and zooming in an image; distance measurement in 3D volume and arbitrary clipping plane; cropping a part of 3D volume etc. The authors point out that the use of a virtual anatomical table should take into account students’ and teachers’ information and digital competence to work with modern virtual equipment and the educational environment of the medical educational institution. Extended clinical cases with unique pathologies in the Sectra Table library contribute to the formation of medical students’ professional competencies. The authors conclude that the use of medical computer programs allows the teacher to organize innovative types of educational activities and to form students’ experimental competence components. The prospects for further research might involve conducting a pedagogical experiment on the effectiveness of using the created system of laboratory works and demonstrations on the basis of Sectra Table F18 Virtual Dissection Table.

Usability Design in Medical Informatics: A Prospective Research Project

This short paper aims to raise awareness of good usability design in medical computer sciences. We present a research plan about developing usability design guidelines for web application development in medical informatics. Following a nimble creation process we shall create a guideline tailored for software developers, that aims to improve communication between the developer and the medical professional. Results are therefore expected to impact the way applications are being developed within the medical sector.

Use of deep learning for structural analysis of computer tomography images of soil samples

Soil samples from several European countries were scanned using medical computer tomography (CT) device and are now available as CT images. The analysis of these samples was carried out using deep learning methods. For this purpose, a VGG16 network was trained with the CT images (X). For the annotation (y) a new method for automated annotation, ‘surrogate’ learning, was introduced. The generated neural networks (NNs) were subjected to a detailed analysis. Among other things, transfer learning was used to check whether the NN can also be trained to other y-values. Visually, the NN was verified using a gradient-based class activation mapping (grad-CAM) algorithm. These analyses showed that the NN was able to generalize, i.e. to capture the spatial structure of the soil sample. Possible applications of the models are discussed.

SYSTEM ANALYSIS OF THE PROBLEMS OF THE SCIENCE AND TECHNOLOGY FIELD «MEDICAL COMPUTER-AIDED DESIGN»

The article provides a system analysis of many problems that hinder the development of medical computer-aided design systems (CAD), in order to identify the most important problems of the subject area. An analysis is made of the key participant roles of the development and practical use process of medical CAD systems in order to determine the degree of their contribution to the final comprehensive result. The structure of business processes is being developed to ensure the completeness and relevance of the developed problematic model. The results can be useful for researchers and developers of medical computer-aided design systems, for experts of related specialties and potential consumers; for doctors studying or actively using computer modeling in the medical diagnostic process; for students studying medical informatics and students of biotechnological specialties, as well as teachers of relevant disciplines.

Deep learning-enabled medical computer vision

A decade of unprecedented progress in artificial intelligence (AI) has demonstrated the potential for many fields—including medicine—to benefit from the insights that AI techniques can extract from data. Here we survey recent progress in the development of modern computer vision techniques—powered by deep learning—for medical applications, focusing on medical imaging, medical video, and clinical deployment. We start by briefly summarizing a decade of progress in convolutional neural networks, including the vision tasks they enable, in the context of healthcare. Next, we discuss several example medical imaging applications that stand to benefit—including cardiology, pathology, dermatology, ophthalmology–and propose new avenues for continued work. We then expand into general medical video, highlighting ways in which clinical workflows can integrate computer vision to enhance care. Finally, we discuss the challenges and hurdles required for real-world clinical deployment of these technologies.

The impact of jo-education match on graduate salaries and job satisfaction

The paper estimates the determinants and effects of the job–education field match on graduates’ salaries and job satisfaction taking the merged data from the Russian Labour Force Survey and the National Survey of Graduate Employment, both conducted in 2016. The authors use various measures of the horizontal job–education match: the respondents’ self-assessment and the objective measure derived from job and education fields codes from the corresponding classifiers. The analysis has shown that the probability of having a job in accordance with the received education is higher for graduates in the sphere of medical, computer and law sciences. There is a penalty for mismatched from 6% to 13% compared to those working accordingly the received diploma. The higher the degree of the mismatch - the greater the penalty. The size of penalty depends on major and on the match measure used. The study revealed the negative impact of the job–education horizontal mismatch on job satisfaction, which provides some evidence that the mismatch is mostly involuntary.

Towards GFO 2.0: Architecture, Modules and Applications

The General Formal Ontology (GFO) is a top-level ontology that has been developed by the Onto-Med Research Group since the early 2000s. Since that time several new theoretical results have been achieved as well as numerous projects have utilized the ontology, especially in complex domains such as bioinformatics and medical computer science. This leads to the need for an up-to-date overview of GFO and access to its applications. This paper represents the first step towards introducing the GFO 2.0 framework, which aims at the integration of the work that is already present, but scattered in various publications, and its provision as a ready-to-use and reusable framework. For this purpose we summarize key features of GFO so far, outline a novel modular architecture and survey first modules for GFO 2.0, linking to applications. Finally, a rigorous and systematic development process is indicated.