Clinical trials in the modern period raise a number of moral and ethical concerns. We need to look at AI-based clinical trials from a range of different moral vantage points if we want to increase their effectiveness in terms of human rights, human value issues, and human safety. “Doing no harm and uplifting human freedom,…
There are a number of risks associated with the use of AI chatbots in healthcare, including: Lack of accuracy: AI chatbots may not have access to the same level of information or expertise as a human healthcare professional, which could lead to inaccurate or incomplete information being provided to patients. Biasness: AI chatbots may be…
Value-driven AI in healthcare refers to the use of artificial intelligence (AI) technology that is designed to align with the values and goals of the healthcare system and its stakeholders. This approach emphasizes the importance of considering the ethical, social, and economic implications of AI in healthcare, and ensuring that the technology is used in…
One goal of value-driven AI is to prevent healthcare-associated infections at the earliest stages and to ensure healthcare for everyone. From both a data science and a medical point of view, hospital infection control is an interesting and difficult research topic. Machine learning for clinicians and infection management covers a wide range of fields. AI is…
Decentralized clinical trials (DCTs) are a new approach to clinical research that leverages artificial intelligence (AI) and other technologies to reduce the cost and complexity of traditional clinical trials. DCTs enable researchers to collect data from multiple sites, often in different countries, while maintaining high standards of data quality and patient safety. DCTs have the…
