AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

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[Expert consensus on ethical requirements for artificial intelligence (AI) processing medical data].

Sheng li xue bao : [Acta physiologica Sinica]
As artificial intelligence technology rapidly advances, its deployment within the medical sector presents substantial ethical challenges. Consequently, it becomes crucial to create a standardized, transparent, and secure framework for processing medi...

Securing a Generative AI-Powered Healthcare Chatbot.

Studies in health technology and informatics
In Generative Artificial Intelligence (AI), Large Language Models (LLMs) like GPT-4, Gemini, Claude, and Llama, significantly impact healthcare by aiding in patient care, medical research, and administrative tasks. AI-powered chatbots offer real-time...

Studying Privacy Aspects of Learned Knowledge Bases in the Context of Synthetic and Medical Data.

Studies in health technology and informatics
INTRODUCTION: Retrieving comprehensible rule-based knowledge from medical data by machine learning is a beneficial task, e.g., for automating the process of creating a decision support system. While this has recently been studied by means of exceptio...

Optimizing Data Extraction: Harnessing RAG and LLMs for German Medical Documents.

Studies in health technology and informatics
In the field of medical data analysis, converting unstructured text documents into a structured format suitable for further use is a significant challenge. This study introduces an automated local deployed data privacy secure pipeline that uses open-...

How Data Infrastructure Deals with Bias Problems in Medical Imaging.

Studies in health technology and informatics
The paper discusses biases in medical imaging analysis, particularly focusing on the challenges posed by the development of machine learning algorithms and generative models. It introduces a taxonomy of bias problems and addresses them through a data...

Secure Extraction of Personal Information from EHR by Federated Machine Learning.

Studies in health technology and informatics
Secure extraction of Personally Identifiable Information (PII) from Electronic Health Records (EHRs) presents significant privacy and security challenges. This study explores the application of Federated Learning (FL) to overcome these challenges wit...

Methods and Algorithms of Ensuring Data Privacy in AI-Based Healthcare Systems and Technologies.

Studies in health technology and informatics
This project seeks to devise novel algorithms and techniques leveraged in healthcare to guarantee data privacy in AI-powered systems. To bolster its credibility, the study review presents various modern approaches and technologies used to preserve da...

[Artificial intelligence in emergency radiology: fiction or reality?].

Revue medicale suisse
Artificial intelligence (AI) is a rapidly advancing technology in our society. The emergency radiology is an area facing an increase of the number of imaging studies and associated to the necessity to promptly deliver an accurate interpretation. The ...

A health-conformant reading of the GDPR's right not to be subject to automated decision-making.

Medical law review
As the use of Artificial Intelligence (AI) technologies in healthcare is expanding, patients in the European Union (EU) are increasingly subjected to automated medical decision-making. This development poses challenges to the protection of patients' ...

Assessing the Impact of Federated Learning and Differential Privacy on Multi-centre Polyp Segmentation.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Federated Learning (FL) is emerging in the medical field to address the need for diverse datasets while complying with data protection regulations. This decentralised learning paradigm allows hospitals (clients) to train machine learning models local...