ALL classification using neural ensemble and memetic deep feature optimization.

Acute lymphoblastic leukemia (ALL) is a fatal blood disorder characterized by the excessive proliferation of immature white blood cells, originating in the bone marrow. An effective prognosis and treatment of ALL calls for its accurate and timely detection. Deep convolutional neural networks (CNNs) have shown promising results in digital pathology.

Digital Innovations for Occupational Safety: Empowering Workers in Hazardous Environments.

Background: The quest to increase safety awareness, make job sites safer, and promote decent work for all has led to the utilization of digital technologies in hazardous occupations. This study investigated the use of digital innovations for safety and health management in hazardous industries. The key challenges and recommendations associated with such use were also explored.

Automated deep bottleneck residual 82-layered architecture with Bayesian optimization for the classification of brain and common maternal fetal ultrasound planes.

Despite a worldwide decline in maternal mortality over the past two decades, a significant gap persists between low- and high-income countries, with 94% of maternal mortality concentrated in low and middle-income nations. Ultrasound serves as a prevalent diagnostic tool in prenatal care for monitoring fetal growth and development. Nevertheless, acquiring standard fetal ultrasound planes with accurate anatomical structures proves challenging and time-intensive, even for skilled sonographers.

Run! This road has no ending! A systematic review of PLS-SEM application in strategic management research among developing nations.

Partial least squares structural equation modelling (PLS-SEM) is emerging as a prominent methodological tool in strategic management research. Although it offers various advancements to stay relevant with growing research needs, the pace of PLS-SEM adoption may differ in different parts of the world. In this paper, we conducted a systematic review using the PRISMA framework and extracted from the top-ranking strategic management journals 120 articles published between 2011 and 2022 that presented a microscopic view on developing nations.

Early-stage pregnancy recognition on microblogs: Machine learning and lexicon-based approaches.

Pregnancy carries high medical and psychosocial risks that could lead pregnant women to experience serious health consequences. Providing protective measures for pregnant women is one of the critical tasks during the pregnancy period. This study proposes an emotion-based mechanism to detect the early stage of pregnancy using real-time data from Twitter.

Determinants of cloud computing integration and its impact on sustainable performance in SMEs: An empirical investigation using the SEM-ANN approach.

Although extant literature has thoroughly investigated the incorporation of cloud computing services, examining their influence on sustainable performance, particularly at the organizational level, is insufficient. Consequently, the present research aims to assess the factors that impact the integration of cloud computing within small and medium-sized enterprises (SMEs) and its subsequent effects on environmental, financial, and social performance. The data were collected from 415 SMEs and were analyzed using a hybrid SEM-ANN approach.

An Innovative Random-Forest-Based Model to Assess the Health Impacts of Regular Commuting Using Non-Invasive Wearable Sensors.

Regular commutes to work can cause chronic stress, which in turn can cause a physical and emotional reaction. The recognition of mental stress in its earliest stages is very necessary for effective clinical treatment. This study investigated the impact of commuting on human health based on qualitative and quantitative measures.

The Impact of Social Media Shared Health Content on Protective Behavior against COVID-19.

The use of social media has increased during the COVID-19 pandemic because people are isolated and working from home. The use of social media enhances information exchange in society and may influence public protective behavior against the COVID-19 pandemic. The purpose of this study is to identify the factors affecting public protective behavior when relying on COVID-19 pandemic-related content shared on social media.

A non-invasive machine learning mechanism for early disease recognition on Twitter: The case of anemia.

Social media sites, such as Twitter, provide the means for users to share their stories, feelings, and health conditions during the disease course. Anemia, the most common type of blood disorder, is recognized as a major public health problem all over the world. Yet very few studies have explored the potential of recognizing anemia from online posts.

Users' intention to continue using mHealth services: A DEMATEL approach during the COVID-19 pandemic.

The coronavirus disease 2019 (COVID-19) has changed the way we use and perceive online services. This study examined the influence of service quality factors during COVID-19 on individuals' intention to continue use mHealth services. A decision-making trial and evaluation laboratory (DEMATEL) approach was used to identify and analyse the relationships between service quality and individuals' intention to continue use mHealth during the COVID-19 pandemic.

Customer relationship management systems (CRMS) in the healthcare environment: A systematic literature review.

Customer relationship management (CRM) is an innovative technology that seeks to improve customer satisfaction, loyalty, and profitability by acquiring, developing, and maintaining effective customer relationships and interactions with stakeholders. Numerous researches on CRM have made significant progress in several areas such as telecommunications, banking, and manufacturing, but research specific to the healthcare environment is very limited. This systematic review aims to categorise, summarise, synthesise, and appraise the research on CRM in the healthcare environment, considering the absence of coherent and comprehensive scholarship of disparate data on CRM.

Telemedicine use in Sub-Saharan Africa: Barriers and policy recommendations for Covid-19 and beyond.

Background: Telemedicine has been a useful healthcare alternative in the fight to contain the recent Covid-19 global pandemic. Yet the extent of its application and efficacy as an alternative route for healthcare provision remains a major concern for clinicians and patients.

Objective: This study sought to identify barriers to the successful implementation of telemedicine in Sub-Saharan African (SSA) countries.

Telemedicine in Middle Eastern countries: Progress, barriers, and policy recommendations.

Background: Despite attempts to reform the healthcare delivery system in the Middle East, expectations for its progress have been-and for some still are-somewhat slow.

Objective: This study reviewed progress in the use and adoption of telemedicine in Middle Eastern countries. The key dimensions affecting the progress of telemedicine in these countries were identified.

An Enhanced Source Location Privacy based on Data Dissemination in Wireless Sensor Networks (DeLP).

Wireless Sensor Network is a network of large number of nodes with limited power and computational capabilities. It has the potential of event monitoring in unattended locations where there is a chance of unauthorized access. The work that is presented here identifies and addresses the problem of eavesdropping in the exposed environment of the sensor network, which makes it easy for the adversary to trace the packets to find the originator source node, hence compromising the contextual privacy.