Sara Gerke
Biographic Data
| ID | 6960360 |
|---|---|
| NAME | Sara Gerke |
| GIVEN NAMES | Sara |
| FAMILY NAME | Gerke |
| SIGNATURE | GERKE S |
| AFFILIATIONS | Dickinson College |
| ORCID | 0000-0002-5718-3982 |
| VERIFIED | Yes |
| TOTAL WORKS | 5 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 5 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2020 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
How Should We Think About Ambient Listening and Transcription Technologies’ Influences on EHR Documentation and Patient-Clinician Conversations
This commentary on a case analyzes how integrating ambient listening and transcription technologies powered by artificial intelligence into the electronic health record documentation process influences documentation practices and clinical encounters. The commentary offers best-practice recommendations for informed consent processes and patient-clinician relationship formation
Synthetic Health Data
Researchers and practitioners are increasingly using machine‐generated synthetic data as a tool for advancing health science and practice, by expanding access to health data while—potentially—mitigating privacy and related ethical concerns around data sharing. While using synthetic data in this way holds promise, we argue that it also raises significant ethical, legal, and policy concerns, including persistent privacy and security problems, accur…
“I’d feel like someone was watchin’ me… watching for a good reason”
On Assessing Trustworthy AI in Healthcare. Machine Learning as a Supportive Tool to Recognize Cardiac Arrest in Emergency Calls
Artificial Intelligence (AI) has the potential to greatly improve the delivery of healthcare and other services that advance population health and wellbeing. However, the use of AI in healthcare also brings potential risks that may cause unintended harm. To guide future developments in AI, the High-Level Expert Group on AI set up by the European Commission (EC), recently published ethics guidelines for what it terms “trustworthy” AI. These guidel…
AI Surveillance during Pandemics
Artificial intelligence surveillance can be used to diagnose individual cases, track the spread of Covid‐19, and help provide care. The use of AI for surveillance purposes (such as detecting new Covid‐19 cases and gathering data from healthy and ill individuals) in a pandemic raises multiple concerns ranging from privacy to discrimination to access to care. Luckily, there exist several frameworks that can help guide stakeholders, especially physi…
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AI Surveillance during Pandemics
Artificial intelligence surveillance can be used to diagnose individual cases, track the spread of Covid‐19, and help provide care. The use of AI for surveillance purposes (such as detecting new Covid‐19 cases and gathering data from healthy and ill individuals) in a pandemic raises multiple concerns ranging from privacy to discrimination to access to care. Luckily, there exist several frameworks that can help guide stakeholders, especially physi…
On Assessing Trustworthy AI in Healthcare. Machine Learning as a Supportive Tool to Recognize Cardiac Arrest in Emergency Calls
Artificial Intelligence (AI) has the potential to greatly improve the delivery of healthcare and other services that advance population health and wellbeing. However, the use of AI in healthcare also brings potential risks that may cause unintended harm. To guide future developments in AI, the High-Level Expert Group on AI set up by the European Commission (EC), recently published ethics guidelines for what it terms “trustworthy” AI. These guidel…
“I’d feel like someone was watchin’ me… watching for a good reason”
Synthetic Health Data
Researchers and practitioners are increasingly using machine‐generated synthetic data as a tool for advancing health science and practice, by expanding access to health data while—potentially—mitigating privacy and related ethical concerns around data sharing. While using synthetic data in this way holds promise, we argue that it also raises significant ethical, legal, and policy concerns, including persistent privacy and security problems, accur…
How Should We Think About Ambient Listening and Transcription Technologies’ Influences on EHR Documentation and Patient-Clinician Conversations
This commentary on a case analyzes how integrating ambient listening and transcription technologies powered by artificial intelligence into the electronic health record documentation process influences documentation practices and clinical encounters. The commentary offers best-practice recommendations for informed consent processes and patient-clinician relationship formation
Computer Science (4 works) · Medicine (4 works) · Artificial Intelligence in Healthcare and Education (3 works) · Health care (3 works) · Internet privacy (3 works) · Law (3 works) · Political science (3 works) · Alternative medicine (2 works) · Data sharing (2 works) · Engineering (2 works)