Generative artificial intelligence (AI) has emerged as a groundbreaking force promising to revolutionize various industries, and one area where its potential is particularly promising is healthcare. From drug discovery to personalized medicine, generative AI is reshaping the landscape of healthcare, offering innovative solutions that have the potential to improve patient outcomes, accelerate research, and optimize medical practices. Fierce Healthcare brought this interesting topic to our attention in their article, “Generative AI expected to take off in 2024, but concerns linger over cost, reliability and security.”
Generative AI may transform healthcare into a more personalized, efficient, and effective system. From drug discovery to patient care, the applications of generative AI are diverse and impactful. As the healthcare industry continues to embrace these innovations, collaboration between AI researchers, healthcare professionals, and policymakers is crucial to navigating the ethical considerations and maximizing the positive impact of generative AI on the well-being of patients worldwide. The future of healthcare is being shaped by the innovative capabilities of generative AI, opening new frontiers for medical research, diagnosis, and treatment.
The biggest challenge is that most organizations including healthcare have little knowledge regarding how AI systems make decisions and how to interpret AI and machine learning results. Explainable AI allows users to comprehend and trust the results and output created by machine learning algorithms. Explainable AI is used to describe an AI model, its expected impact, and its potential biases. Explainability becomes critical when the results can have an impact on data security or safety.
Melody K. Smith
| Data Harmony is an award-winning semantic suite that leverages explainable AI. |
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