Alle Papers – KI in der Medizin

Opening the Black Box: The Promise and Limitations of Explainable Machine Learning in Cardiology

Multi-institutional Deep Learning Modeling Without Sharing Patient Data: A Feasibility Study on Brain Tumor Segmentation

Applications of artificial neural networks in health care organizational decision-making: A scoping review

Snorkel: rapid training data creation with weak supervision.

A Perspective on Explainable Artificial Intelligence Methods: SHAP and LIME

In AI We Trust: Ethics, Artificial Intelligence, and Reliability

Artificial Intelligence (AI) Student Assistants in the Classroom: Designing Chatbots to Support Student Success

ChatGPT and large language models in academia: opportunities and challenges

Notions of explainability and evaluation approaches for explainable artificial intelligence

Unlocking the Power of ChatGPT: A Framework for Applying Generative AI in Education

Emerging challenges in AI and the need for AI ethics education

Algorithmic fairness in artificial intelligence for medicine and healthcare

The Hong Kong Principles for assessing researchers: Fostering research integrity

There is a blind spot in AI research

ChatGPT for Good? On Opportunities and Challenges of Large Language Models for Education

A Review on Fairness in Machine Learning

Federated Learning for Healthcare: Systematic Review and Architecture Proposal

Surgical data science for next-generation interventions

Slave to the Algorithm? Why a 'right to an explanation' is probably not the remedy you are looking for

How to Read Articles That Use Machine Learning

Bias in artificial intelligence algorithms and recommendations for mitigation

The role of ChatGPT in higher education: Benefits, challenges, and future research directions

Privacy-Preserving Federated Brain Tumour Segmentation

The next generation of evidence-based medicine

On the ethics of algorithmic decision-making in healthcare