Shaping Future Doctors’ Minds: Effects of Biological and Social Models on Medical Students’ Views on Depression

Kostić, Milutin; Radanović, Ana; Jovanovic, S Bosko

doi:10.1007/s40596-021-01515-x

Cited by 2 publications

(2 citation statements)

References 36 publications

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“…The parameter's keywords include student, medical, nursing, medical student, education, nursing student, clinical, undergraduate, patient, medical education, health, nurse, medical school, medicine, education medical, practice, nursing education, study education nursing, and interprofessional. The dimensions covered by this parameter include the challenges of medical education including cost [126], distance learning [127] and practical training [128], how to improve family medicine [129], how to improve homecare and the nursing profession [130], how to improve medical education and profession [127], and simulations and other methods based on the emerging technologies to improve healthcare [131].…”

Section: Healthcare Provisionmentioning

confidence: 99%

Smart Homes and Families to Enable Sustainable Societies: A Data-Driven Approach for Multi-Perspective Parameter Discovery Using BERT Modelling

et al. 2022

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Homes are the building block of cities and societies and therefore smart homes are critical to establishing smart living and are expected to play a key role in enabling smart, sustainable cities and societies. The current literature on smart homes has mainly focused on developing smart functions for homes such as security and ambiance management. Homes are composed of families and are inherently complex phenomena underlined by humans and their relationships with each other, subject to individual, intragroup, intergroup, and intercommunity goals. There is a clear need to understand, define, consolidate existing research, and actualize the overarching roles of smart homes, and the roles of smart homes that will serve the needs of future smart cities and societies. This paper introduces our data-driven parameter discovery methodology and uses it to provide, for the first time, an extensive, fairly comprehensive, analysis of the families and homes landscape seen through the eyes of academics and the public, using over a hundred thousand research papers and nearly a million tweets. We developed a methodology using deep learning, natural language processing (NLP), and big data analytics methods (BERT and other machine learning methods) and applied it to automatically discover parameters that capture a comprehensive knowledge and design space of smart families and homes comprising social, political, economic, environmental, and other dimensions. The 66 discovered parameters and the knowledge space comprising 100 s of dimensions are explained by reviewing and referencing over 300 articles from the academic literature and tweets. The knowledge and parameters discovered in this paper can be used to develop a holistic understanding of matters related to families and homes facilitating the development of better, community-specific policies, technologies, solutions, and industries for families and homes, leading to strengthening families and homes, and in turn, empowering sustainable societies across the globe.

show abstract

Section: Healthcare Provisionmentioning

confidence: 99%

Smart Homes and Families to Enable Sustainable Societies: A Data-Driven Approach for Multi-Perspective Parameter Discovery Using BERT Modelling

et al. 2022

View full text Add to dashboard Cite

show abstract

“…The parameter's keywords include student, medical, nursing, medical student, education, nursing student, clinical, undergraduate, patient, medical education, health, nurse, medical school, medicine, education medical, practice, nursing education, study education nursing, and interprofessional. The dimensions covered by this parameter include the challenges of medical education including cost [149], distance learning [150] and practical training [151], how to improve family medicine [152], how to improve homecare and the nursing profession [153], how to improve medical education and profession [150], and simulations and other methods based on the emerging technologies to improve healthcare [154]. For example, for medical education, Walsh [149] stressed the importance to consider how to control costs or how to improve value for money as they believe it continues to be too expensive for students and their families to receive medical education.…”

Section: Healthcare Provisionmentioning

confidence: 99%

Smart Homes and Families to Enable Sustainable Societies: A Data-Driven Approach for Multi-Perspective Parameter Discovery using BERT Modelling

Alqahtani¹,

Janbi²,

Sharaf³

et al. 2022

Preprint

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Technological advancements and innovations have profoundly changed the lives of people giving rise to smart environments, cities, and societies. As homes are the building block of cities and societies, smart homes are critical to establishing smart living and are expected to play a key role in enabling smart cities and societies. The current academic literature and commercial advancements on smart homes have mainly focused on developing and providing smart functions for homes to provide security management and facilitate the residents in their various activities such as ambiance management. Homes are much more than physical structures, buildings, appliances, operational machines, and systems. Homes are composed of families and are inherently complex phenomena underlined by humans and their relationships with each other, subject to individual, intragroup, intergroup, and intercommunity goals. There is a clear need to understand, define, consolidate existing research, and actualize the overarching roles of smart homes, the roles of smart homes that would serve the needs of future smart cities and societies. This paper introduces our data-driven parameter discovery methodology and uses it to provide, for the first time, an extensive, rather fairly comprehensive, analysis of the families and homes landscape seen through the eyes of academics and the public using over a hundred thousand research papers and nearly a million tweets. We develop a methodology using deep learning, natural language processing (NLP), and big data analytics methods and apply it to automatically discover parameters that capture a comprehensive knowledge and design space of smart families and homes comprising social, political, economic, environmental, and other dimensions. The 66 discovered parameters and the knowledge space comprising 100s of dimensions are explained by reviewing and referencing over 300 articles from the academic literature and tweets. The knowledge and parameters discovered in this paper can be used to develop a holistic understanding of matters related to families and homes facilitating the development of better, community-specific, policies, technologies, solutions, and industries for families and homes, leading to strengthening families and homes, and in turn, empowering sustainable societies across the globe.

show abstract

Shaping Future Doctors’ Minds: Effects of Biological and Social Models on Medical Students’ Views on Depression

Cited by 2 publications

References 36 publications

Smart Homes and Families to Enable Sustainable Societies: A Data-Driven Approach for Multi-Perspective Parameter Discovery Using BERT Modelling

Smart Homes and Families to Enable Sustainable Societies: A Data-Driven Approach for Multi-Perspective Parameter Discovery Using BERT Modelling

Smart Homes and Families to Enable Sustainable Societies: A Data-Driven Approach for Multi-Perspective Parameter Discovery using BERT Modelling

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