Biomedical-named entity recognition (bNER) is critical in biomedical informatics. It identifies biomedical entities with special meanings, such as people, places, and organizations, as predefined semantic types in electronic health records (EHR). bNER is essential for discovering novel knowledge using computational methods and Information Technology. Early bNER systems were configured manually to include domain-specific features and rules. However, these systems were limited in handling the complexity of the biomedical text. Recent advances in deep learning (DL) have led to the development of more powerful bNER systems. DL-based bNER systems can learn the patterns of biomedical text automatically, making them more robust and efficient than traditional rule-based systems. This paper reviews the healthcare domain of bNER, using DL techniques and artificial intelligence in clinical records, for mining treatment prediction. bNER-based tools are categorized systematically and represent the distribution of input, context, and tag (encoder/decoder). Furthermore, to create a labeled dataset for our machine learning sentiment analyzer to analyze the sentiment of a set of tweets, we used a manual coding approach and the multi-task learning method to bias the training signals with domain knowledge inductively. To conclude, we discuss the challenges facing bNER systems and future directions in the healthcare field.

Purpose: Meal ordering apps (MOAs) have transformed the customers' dining habits, particularly during mobility restrictions of the COVID-19 pandemic. Under the theoretical cover of the extended stimulus–organism–response (SOR) model, this paper attempts to explore the critical antecedents and outcomes of customer MOA engagement which predict the continuous purchase intentions using these apps. A multigroup analysis is conducted to investigate the difference between the hypothesized relationships between the Chinese and Indonesian consumers.Design/methodology/approach: A mixed-method approach, including a systematic literature review, an open-ended essay (qualitative) with 139 MOA users and an online survey (quantitative) with 1,207 MOA users in total, was used for hypotheses testing.Findings: The structural equation model results revealed that customer MOA experience factors such as mobile online reviews (MR), food quality (FQ), restaurant reputation (RR), service quality and system quality (SyQ) are the absolute positive factors that influence customer MOA cognitive, affective and behavioral engagement, which in turn affect continuous purchase intentions. The multigroup analysis results reveal that Chinese customers prioritized MR and FQ for customer MOA engagement (cognitive, affective and behavioral). Comparatively, Indonesian customers placed most importance on RR and SyQ.Originality/value: Considering a market-specific setting and based on the extended SOR framework, this study is one of the first to take a comprehensive look at the critical antecedents and outcome of multidimensional customer MOA engagement in the developing countries’ (China and Indonesia) online to offline meal delivery context. Further, this study investigates the customer continuous purchase intentions as an outcome of MOA engagement during the COVID-19 pandemic. The findings also reveal the differences in consumer behavior across the two developing but culturally diverse countries samples during the pandemic.

Background: Pakistan is the world’s sixth most populated country, with a population of approximately 208 million people. Despite this, just 25% of legitimate couples say they have used modern contraceptive methods. A large body of literature has indicated that sexual satisfaction is a complex and multifaceted concept, since it involves physical and cultural components. The purpose of this study is to investigate the impact of influencing factors in terms of contraceptive self-efficacy (CSE), contraceptive knowledge, and spousal communication on the adoption of modern contraceptive methods for family planning (FP) under the moderating role of perceived barriers. Methods: Data were collected using an adopted questionnaire issued to married women of reproductive age belonging to the Rawalpindi and Neelum Valley regions in Pakistan. The sample consisted of 250 married women of reproductive age. SPSS was used to analyze the respondents’ feedback. Results: The findings draw public attention towards CSE, contraceptive knowledge, and spousal communication, because these factors can increase the usage of modern methods for FP among couples, leading to a reduction in unwanted pregnancies and associated risks. Regarding the significant moderation effect of perceived barriers, if individuals (women) are highly motivated (CSE) to overcome perceived barriers by convincing their husbands to use contraceptives, the probability to adopt modern contraceptive methods for FP practices is increased. Conclusions: Policymakers should formulate strategies for the involvement of males by designing male-oriented FP program interventions and incorporating male FP workers to reduce communication barriers between couples. Future research should address several other important variables, such as the desire for additional child, myths/misconceptions, fear of side effects, and partner/friend discouragement, which also affect the adoption of modern contraceptive methods for FP practices.

Purpose: This study examines how service feedback and physician popularity affect physician demand in the context of virtual healthcare environment. Based on the signaling theory, the critical factor of environment uncertainty (i.e. disease risk) and its impact on physician demand is also investigated. Further, the research on the endogeneity of online reviews in healthcare is also examined in the current study.Design/methodology/approach: A secondary data econometric analysis using 3-wave data sets of 823 physicians obtained from two PRWs (Healthgrades and Vitals) was conducted. The analysis was run using the difference-in-difference method to consider physician and website-specific effects.Findings: The study's findings indicate that physician popularity has a stronger positive effect on physician demand compared with service feedback. Improving popularity leads to a relative increase in the number of appointments, which in turn enhance physician demand. Further, the impact of physician popularity on physician demand is positively mitigated by the disease risk.Originality/value: The authors' research contributes to a better understanding of the signaling transmission mechanism in the online healthcare environment. Further, the findings provide practical implications for key stakeholders into how an efficient feedback and popularity mechanism can be built to enhance physician service outcomes in order to maximize the financial efficiency of physicians.