AIMC Topic: Privacy
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Ensuring privacy protection in the era of big laparoscopic video data: development and validation of an inside outside discrimination algorithm (IODA).
Surgical endoscopy
May 5, 2023
BACKGROUND: Laparoscopic videos are increasingly being used for surgical artificial intelligence (AI) and big data analysis. The purpose of this study was to ensure data privacy in video recordings of laparoscopic surgery by censoring extraabdominal ...
Commitments for Ethically Responsible Sourcing, Use, and Reuse of Patient Data in the Digital Age: Cocreation Process.
Journal of medical Internet research
May 5, 2023
BACKGROUND: Personal information, including health-related data, may be used in ways we did not intend when it was originally shared. However, the organizations that collect these data do not always have the necessary social license to use and share ...
Privacy risks of whole-slide image sharing in digital pathology.
Nature communications
May 4, 2023
Access to large volumes of so-called whole-slide images-high-resolution scans of complete pathological slides-has become a cornerstone of the development of novel artificial intelligence methods in pathology for diagnostic use, education/training of ...
Neural gradient boosting in federated learning for hemodynamic instability prediction: towards a distributed and scalable deep learning-based solution.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Apr 29, 2023
Federated learning (FL) is a privacy preserving approach to learning that overcome issues related to data access, privacy, and security, which represent key challenges in the healthcare sector. FL enables hospitals to collaboratively learn a shared p...
Privacy preserving for AI-based 3D human pose recovery and retargeting.
ISA transactions
Apr 24, 2023
As an essential research task in artificial intelligence (AI), the estimation of 3D human poses has important application value in virtual reality, medical diagnosis, athlete training and other fields. However, human pose recovery and retargeting req...
A Large-scale Synthetic Pathological Dataset for Deep Learning-enabled Segmentation of Breast Cancer.
Scientific data
Apr 21, 2023
The success of training computer-vision models heavily relies on the support of large-scale, real-world images with annotations. Yet such an annotation-ready dataset is difficult to curate in pathology due to the privacy protection and excessive anno...
Privacy-preserving artificial intelligence in healthcare: Techniques and applications.
Computers in biology and medicine
Apr 5, 2023
There has been an increasing interest in translating artificial intelligence (AI) research into clinically-validated applications to improve the performance, capacity, and efficacy of healthcare services. Despite substantial research worldwide, very ...
Managing Security of Healthcare Data for a Modern Healthcare System.
Sensors (Basel, Switzerland)
Mar 30, 2023
The advent of Artificial Intelligence (AI) and the Internet of Things (IoT) have recently created previously unimaginable opportunities for boosting clinical and patient services, reducing costs and improving community health. Yet, a fundamental chal...
Ethical use of Artificial Intelligence in Health Professions Education: AMEE Guide No. 158.
Medical teacher
Mar 13, 2023
Health Professions Education (HPE) has benefitted from the advances in Artificial Intelligence (AI) and is set to benefit more in the future. Just as any technological advance opens discussions about ethics, so the implications of AI for HPE ethics n...
Persuading Patients Using Rhetoric to Improve Artificial Intelligence Adoption: Experimental Study.
Journal of medical Internet research
Mar 13, 2023
BACKGROUND: Artificial intelligence (AI) can transform health care processes with its increasing ability to translate complex structured and unstructured data into actionable clinical decisions. Although it has been established that AI is much more e...
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