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Improving the transparency and reliability of observational studies through registration

Florian Naudet and colleagues argue that routine registration of observational research is needed and suggest how current processes can be adapted to facilitate it From the use of booster doses against covid-191 to approval of novel cancer therapies,2 health authorities and health technology assessment bodies are increasingly relying on non-randomised trials and observational studies. The methodological problems of observational studies, such as residual confounding,3 are difficult to resolve, but concerns about transparency and reliability can be reduced through registration. Registration is an open science practice whereby research hypotheses, elements of study design, and planned statistical analyses are prespecified, preferably in a centralised repository. Registration has become the norm for clinical trials (interventional studies),4 and some have called for it to be adopted for observational studies.56 However, opponents argue that systematic registration is unrealistic, unnece

Re: A commitment to act on data sharing: Acting on the moral responsibility of a noble promise

Re: A commitment to act on data sharing: Acting on the moral responsibility of a noble promise
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Generative AI for medical research

Protecting against misuse without forfeiting the potential benefits is key The global market for artificial intelligence (AI) for healthcare is booming. Currently valued at $15bn (£12bn; €14bn), it is expected to near $200bn by 2030.12 Public sector spending on AI for healthcare is also on the rise. The UK government, for example, has already invested more than £123m in AI for healthcare technologies.3 Of course, previous AI “summers” were followed swiftly by AI “winters,” when the gap between expectations and the reality of AI grew too wide. This summer’s heat and longevity can largely be attributed to the advent of generative AI. Generative AI is a type of machine learning capable of generating data in a range of formats (including text, image, audio, video, or code) and adapting to new tasks in real time, following simple text based prompts. These capabilities make generative AI flexible, as one “model” (for example, ChatGPT or DALL-E) can be used for a variety o

New UK clinical trials legislation will prioritise transparency

New UK clinical trials legislation will prioritise transparency
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Commentary: Why the courts are right to rule against LinkedIn in battle over data scraping – GeekWire

Commentary: Why the courts are right to rule against LinkedIn in battle over data scraping – GeekWire
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