Explaining Machine Learning Models for Clinical Gait Analysis

Machine Learning (ML) is increasingly used to support decision-making in the healthcare sector. While ML approaches provide promising results with regard to their classification performance, most share a central limitation, their black-box character. This article investigates the usefulness of Explainable Artificial Intelligence (XAI) methods to increase transparency in automated clinical gait classification based on time series. For this purpose, predictions of state-of-the-art classification methods are explained with a XAI method called Layer-wise Relevance Propagation (LRP). Our main contribution is an approach that explains class-specific characteristics learned by ML models that are trained for gait classification. We investigate several gait classification tasks and employ different classification methods, i.e., Convolutional Neural Network, Support Vector Machine, and Multi-layer Perceptron. We propose to evaluate the obtained explanations with two complementary approaches: a statistical analysis of the underlying data using Statistical Parametric Mapping and a qualitative evaluation by two clinical experts. A gait dataset comprising ground reaction force measurements from 132 patients with different lower-body gait disorders and 62 healthy controls is utilized. Our experiments show that explanations obtained by LRP exhibit promising statistical properties concerning inter-class discriminativity and are also in line with clinically relevant biomechanical gait characteristics.

Mispa count X; The first indigenous indian hematology 3-part analyzer

: Impedance technology was a revolution in the history of Hematology. Mispa Count X is the first indigenous 3-part hematology analyzer in India, which works on the principle of impedance technology. : Performance evaluation of Mispa Count X.: The analyzer produces the measurement results of 18 parameters with throughput of 60 samples per hour. Mispa Count X was compared with benchmark analyzers Coulter DxH 800 and Sysmex XN 1000 to validate its performance. : Mispa Count X exhibited a wide linearity range for WBC, RBC, platelet and hemoglobin. The carry over for WBC, RBC, PLT and Hb was estimated and found to be well within the acceptable limits. The r values (> 0.90) and bias estimation of Mispa Count X on comparing with Coulter DxH 800 and Sysmex XN 1000 were acceptable, except for mid cell counts and for MPV. Mispa Count X exhibited good precision with an acceptable CV% (< 10%). The primary parameters of the stored samples were stable at room temperature for 24 hours. : So we conclude our study by proving that the Mispa Count X would be an affordable-reliable alternative for Indian healthcare sector instead of expensive imported hematology analyzers.

Digitalization of the Japanese Economy by the Example of the Banking Sector: Current Results, Prospects and Problems

Purpose: the purpose of this study is to examine the current state of Japan's digital transformation, with a focus on the banking sector, analyzing specifc examples, identifying obstacles that hinder the achievement of expected results.Methods: the article is based on the analysis of scientifc and analytical materials devoted to the problem of research, a set of general scientific methods is applied, including comparison, scientifc generalization, analogy, etc.Results: the article presents the main trends and current results of digitalization of Japanese banks, provides examples of projects, identifies problematic areas of the implemented policy. A hypothesis is put forward about the key role of the government in the development of new standards for the organization of work, taking into account the use of innovative technologies. For Japan, digitalization is chosen as a key tool to mitigate the current socio-economic situation. Digitalization is already being implemented in the healthcare sector, agriculture, etc. Another sector at the center of digitalization is the fnancial one. Financial technologies form new markets and products. Non-banking companies penetrate into the areas occupied by classical banks, competing and even displacing them.These processes are observed both in Japan and in other countries of the world, including Russia. Therefore, studying the Japanese experience of integrating digital technologies into the fnancial sector is important. Although Russia is among the leaders in the digitalization of the financial sector, it is difcult for fntech companies to break into the Russian market due to pressure from large classical banks, as well as the lack of trust in fntech companies from the population.Conclusions and Relevance: in contrast to the manufacturing sector, digitalization of non-manufacturing areas is slower in Japan. This is due to a shortage of qualifed personnel, fnancial risks, etc. Today, the priority for fnancial institutions remains to create the basis for the introduction of digitalization and improve management efciency. From the point of view of ensuring the stability of the fnancial system, it is expected that the Bank of Japan, together with the government, will encourage initiatives in the feld of fnancial development.

Open Innovation in Times of Crisis: An Overview of the Healthcare Sector in Response to the COVID-19 Pandemic

The COVID-19 pandemic has caused huge and disruptive technological changes in the healthcare sector, transforming the way businesses and societies function. To respond to the global health crisis, there have been numerous innovation projects in the healthcare sector, including the fast design and manufacturing of personal protective equipment (PPE) and medical devices, and testing, treatment, and vaccine technologies. Many of these innovative activities happen beyond organizational boundaries with collaboration and open innovation. In this paper, we review the current literature on open innovation strategy during the pandemic and adopt the co-evolution view of business ecosystems to address the context of change. Based on a detailed exploration of the COVID-19-related technologies in the UK and global healthcare sectors, we identify the key emerging themes of open innovation in crisis. Further discussions are conducted in relation to each theme. Our results and analysis can help provide policy recommendations for the healthcare sector, businesses, and society to recover from the crisis.

Blockchain-Based Digital Twins Collaboration for Smart Pandemic Alerting: Decentralized COVID-19 Pandemic Alerting Use Case

Emerging technologies such as digital twins, blockchain, Internet of Things (IoT), and Artificial Intelligence (AI) play a vital role in driving the industrial revolution in all domains, including the healthcare sector. As a result of COVID-19 pandemic outbreak, there is a significant need for medical cyber-physical systems to adopt these emerging technologies to combat COVID-19 paramedic crisis. Also, acquiring secure real-time data exchange and analysis across multiple participants is essential to support the efforts against COVID-19. Therefore, we have introduced a blockchain-based collaborative digital twins framework for decentralized epidemic alerting to combat COVID-19 and any future pandemics. The framework has been proposed to bring together the existing advanced technologies (i.e., blockchain, digital twins, and AI) and then provide a solution to decentralize epidemic alerting to combat COVID-19 outbreaks. Also, we have described how the conceptual framework can be applied in the decentralized COVID-19 pandemic alerting use case.

MORTALITY RATES AND INFECTION WITH THE SARS-COV-2 VIRUS AMONG MEDICAL PERSONNEL IN KAZAKHSTAN AND AROUND THE WORLD DURING THE COVID-19 PANDEMIC

В сфере здравоохранения во избежание стагнации во время пандемии необходимо максимально обезопасить медицинский персонал и проводить большое количество профилактических мероприятий. Как доказано во многих научных статьях, главной мерой защиты медицинских работников от заражения и смерти является не только полное и своевременное обеспечение средствами индивидуальной защиты, но и подготовка специальных специалистов, которые научат, как правильно их применять. In the healthcare sector, in order to avoid stagnation during a pandemic, it is necessary to protect medical personnel as much as possible and carry out a large number of preventive measures. As proved in many scientific articles, the main measure to protect medical workers from infection and death is not only the full and timely provision of personal protective equipment, but also the training of special specialists who will teach how to use them correctly.

Implementation of Lean Management in a Multi-Specialist Hospital in Poland and the Analysis of Waste

At the beginning of the 21st century, Lean Management (LM) tools were introduced into the healthcare sector around the world. In Poland, there are still few LM implementations, and they are not of a comprehensive nature. The aim of this article is to present the application of the LM concept in a hospital in Poland as a tool for the identification and analysis of waste and its impact on the process of organizing the provision of medical services on the example of improvements in the process of patient admission. In the period from 1 July 2019 to 31 December 2019, a project of LM implementation was carried out at the Provincial Specialist Hospital in Wroclaw. The project was based on the method of value-stream mapping and 5Why. Standardized interviews (before and after the project) were conducted with people from the hospital management and middle-level managers. The implementation of LM tools resulted in the identification of a number of wastes, which have been divided into groups. The most important waste was paper medical documentation. Its change to an electronic form allowed for a better use of human capital resources; savings included 2.3 nursing positions and 1.09 medical staff positions.