Search Tag: prompt engineering
2025 27 Oct
Large language models (LLMs) can recall extensive medical facts yet still produce unsafe outputs when prompted in ways that conflict with basic logic. Researchers evaluated five frontier LLMs using drug prompts that deliberately misrepresented brand–generic equivalence, a setting where models already have the knowledge to recognise the flaw. The...Read more
2025 27 Oct
Large language models (LLMs) can recall extensive medical facts yet still produce unsafe outputs when prompted in ways that conflict with basic logic. Researchers evaluated five frontier LLMs using drug prompts that deliberately misrepresented brand–generic equivalence, a setting where models already have the knowledge to recognise the flaw. The...Read more
2025 16 Oct
Rapid identification of critical radiology findings is essential as reporting volumes rise and language grows more nuanced. Traditional natural language processing depends on rules or large annotated datasets, which can miss context. General-purpose large language models (LLMs) offer a prompt-driven alternative that may work without retraining....Read more
2025 16 Oct
Rapid identification of critical radiology findings is essential as reporting volumes rise and language grows more nuanced. Traditional natural language processing depends on rules or large annotated datasets, which can miss context. General-purpose large language models (LLMs) offer a prompt-driven alternative that may work without retraining....Read more
2025 16 Oct
Rapid identification of critical radiology findings is essential as reporting volumes rise and language grows more nuanced. Traditional natural language processing depends on rules or large annotated datasets, which can miss context. General-purpose large language models (LLMs) offer a prompt-driven alternative that may work without retraining....Read more
2025 16 Oct
Rapid identification of critical radiology findings is essential as reporting volumes rise and language grows more nuanced. Traditional natural language processing depends on rules or large annotated datasets, which can miss context. General-purpose large language models (LLMs) offer a prompt-driven alternative that may work without retraining....Read more
2025 16 Oct
Rapid identification of critical radiology findings is essential as reporting volumes rise and language grows more nuanced. Traditional natural language processing depends on rules or large annotated datasets, which can miss context. General-purpose large language models (LLMs) offer a prompt-driven alternative that may work without retraining....Read more
2025 18 Sep
Large language models are increasingly embedded in radiology tasks such as report generation, interpretation and workflow optimisation. Their value depends less on model scale alone and more on the clarity, context and structure of the inputs that guide them. Prompt engineering aligns model behaviour with clinical intent, curbs irrelevant outputs...Read more
2025 18 Sep
Large language models are increasingly embedded in radiology tasks such as report generation, interpretation and workflow optimisation. Their value depends less on model scale alone and more on the clarity, context and structure of the inputs that guide them. Prompt engineering aligns model behaviour with clinical intent, curbs irrelevant outputs...Read more
2025 18 Sep
Large language models are increasingly embedded in radiology tasks such as report generation, interpretation and workflow optimisation. Their value depends less on model scale alone and more on the clarity, context and structure of the inputs that guide them. Prompt engineering aligns model behaviour with clinical intent, curbs irrelevant outputs...Read more
2025 24 Aug
Large language models are being integrated into radiology workflows with growing interest, thanks to their ability to perform advanced natural language tasks. These tools support report generation, summarisation, data labelling and clinical decision support. However, their tendency to generate inaccurate or misleading information, often referred...Read more
2025 18 Aug
Large language models (LLMs) are gaining ground in healthcare, where they are used to generate clinical summaries, support decision-making and assist in patient communication. Their ability to synthesise complex medical knowledge into accessible text offers clear advantages, but their reliability is challenged by a phenomenon known as hallucination....Read more
2025 18 Aug
Large language models (LLMs) are gaining ground in healthcare, where they are used to generate clinical summaries, support decision-making and assist in patient communication. Their ability to synthesise complex medical knowledge into accessible text offers clear advantages, but their reliability is challenged by a phenomenon known as hallucination....Read more
2025 22 Jun
Generative AI systems become increasingly integrated into healthcare and everyday decision-making, so the challenge of understanding how these models function has gained urgency. Large language models (LLMs) such as ChatGPT are powerful but often operate as “black boxes”, leaving clinicians wary of trusting their outputs. Concerns about AI-generated...Read more
2025 22 Jun
Generative AI systems become increasingly integrated into healthcare and everyday decision-making, so the challenge of understanding how these models function has gained urgency. Large language models (LLMs) such as ChatGPT are powerful but often operate as “black boxes”, leaving clinicians wary of trusting their outputs. Concerns about AI-generated...Read more
2025 09 Jun
Radiology and pathology reports are central to clinical decision-making and research, yet their unstructured format often hinders automated data analysis. While previous natural language processing techniques have demonstrated some potential in extracting information, they often suffer from limited generalisability, high computational costs and...Read more