Mari S Kannelønning
Datos Biográficos
| ID | 6197041 |
|---|---|
| NOMBRE | Mari S Kannelønning |
| NOMBRES | Mari S |
| APELLIDO | Kannelønning |
| FIRMA | KANNELØNNING M S |
| AFILIACIONES | OsloMet – Oslo Metropolitan University |
| ORCID | 0009-0004-4499-1720 |
| VERIFICADO | Sí |
| TOTAL DE OBRAS | 3 |
| TOTAL DE CITAS | 4 |
| OBRAS COMO AUTOR | 3 |
| OBRAS COMO EDITOR | 0 |
| PRIMER AÑO DE PUBLICACIÓN | 2024 |
| AÑO MÁS RECIENTE DE PUBLICACIÓN | 2025 |
| ÍNDICE H | 2 |
Reflecting on LLM Support in Reflexive Thematic Analysis
The launch of ChatGPT in November 2022 accelerated discussions and research into whether base large language models (LLMs) could increase the efficiency of qualitative analysis phases or even replace qualitative researchers. Reflexive thematic analysis (RTA) is a commonly used method for qualitative text analysis that emphasizes the researcher's subjectivity and reflexivity to enable a situated, in-depth understanding of knowledge generation. Res…
Domesticating AI in medical diagnosis
We consider the anticipated adoption of Artificial Intelligence (AI) in medical diagnosis. We examine how seemingly compelling claims are tested as AI tools move into real-world settings and discuss how analysts can develop effective understandings in novel and rapidly changing settings. Four case studies highlight the challenges of utilising diagnostic AI tools at differing stages in their innovation journey. Two ‘upstream’ cases seeking to demo…
Navigating uncertainties of introducing artificial intelligence (AI) in healthcare
Artificial Intelligence (AI) technologies are expected to solve pressing challenges in healthcare services worldwide. However, the current state of introducing AI is characterised by several issues complicating and delaying their deployments. These issues concern topics such as ethics, regulations, data access, human trust, and limited evidence of AI technologies in real-world clinical settings. They further encompass uncertainties, for instance,…
Domesticating AI in medical diagnosis
We consider the anticipated adoption of Artificial Intelligence (AI) in medical diagnosis. We examine how seemingly compelling claims are tested as AI tools move into real-world settings and discuss how analysts can develop effective understandings in novel and rapidly changing settings. Four case studies highlight the challenges of utilising diagnostic AI tools at differing stages in their innovation journey. Two ‘upstream’ cases seeking to demo…
Navigating uncertainties of introducing artificial intelligence (AI) in healthcare
Artificial Intelligence (AI) technologies are expected to solve pressing challenges in healthcare services worldwide. However, the current state of introducing AI is characterised by several issues complicating and delaying their deployments. These issues concern topics such as ethics, regulations, data access, human trust, and limited evidence of AI technologies in real-world clinical settings. They further encompass uncertainties, for instance,…
Domesticating AI in medical diagnosis
We consider the anticipated adoption of Artificial Intelligence (AI) in medical diagnosis. We examine how seemingly compelling claims are tested as AI tools move into real-world settings and discuss how analysts can develop effective understandings in novel and rapidly changing settings. Four case studies highlight the challenges of utilising diagnostic AI tools at differing stages in their innovation journey. Two ‘upstream’ cases seeking to demo…
Navigating uncertainties of introducing artificial intelligence (AI) in healthcare
Artificial Intelligence (AI) technologies are expected to solve pressing challenges in healthcare services worldwide. However, the current state of introducing AI is characterised by several issues complicating and delaying their deployments. These issues concern topics such as ethics, regulations, data access, human trust, and limited evidence of AI technologies in real-world clinical settings. They further encompass uncertainties, for instance,…
Reflecting on LLM Support in Reflexive Thematic Analysis
The launch of ChatGPT in November 2022 accelerated discussions and research into whether base large language models (LLMs) could increase the efficiency of qualitative analysis phases or even replace qualitative researchers. Reflexive thematic analysis (RTA) is a commonly used method for qualitative text analysis that emphasizes the researcher's subjectivity and reflexivity to enable a situated, in-depth understanding of knowledge generation. Res…
Artificial Intelligence in Healthcare and Education (3 obras) · AI in cancer detection (2 obras) · Artificial Intelligence (2 obras) · Artificial Intelligence in Healthcare (2 obras) · Computer Science (2 obras) · Business (1 obra) · Clinical Reasoning and Diagnostic Skills (1 obra) · Engineering (1 obra) · Engineering ethics (1 obra) · Exploratory research (1 obra)