Start with the patient’s question. Turn global medical research into reliable evidence that fits the individual.
Trusted evidence · Human–AI collaboration · Continuous improvementExamines the steps that require evaluation between medical answers, retrieval, synthesis, updating and individual decisions.
Large Language Models in Medical Decision Making from Clinical Answers to Living Evidence
Read the manuscript20,399 deduplicated records and 445 studies, illustrating research scale, synthesis methods and reviewable source records.
Preoperative Social Connection and Postoperative Outcomes in Adults Undergoing Surgery: A Systematic Review and Meta-analysis
Read the manuscriptLinks original sources, effect selection, statistical contributions, corrections and released versions; developed and internally evaluated in one review case.
An auditable evidence system for large language model-assisted systematic reviews: development and internal evaluation
Read the manuscriptProposes an Evidence OS framework that starts with patient goals, comorbidities and questions, organises synthesis and research, and brings findings back to patient decisions.
Large language models for patient-centred evidence generation and use
Read the manuscriptEach result becomes a foundation for the next study. Explore progress, next steps and research basis.
How should evidence be organised around patient goals and comorbidity?
A patient-centred framework manuscript organises evidence generation and use around comorbidity, patient goals and concrete questions.
Translate the framework into measurable tasks and evaluation criteria.
Which steps from clinical answers to living evidence have been evaluated?
A published review manuscript examines evidence across medical dialogue, retrieval, synthesis, updating and individual decisions.
Refine the programme and its evaluation requirements through continuing literature tracking.
Can large literature collections become reviewable, reusable evidence?
The social-connection review contains 20,399 deduplicated records and 445 studies; 72 enter at least one quantitative synthesis.
Assess reuse in comorbidity research and retain evidence that cannot be pooled.
Can each conclusion be traced to its sources, revisions and responsibilities?
An auditable system was developed and internally evaluated in one review: 50 root-cause events, 46 resolved and 4 retained limitations.
Run independent comparative evaluations of errors, costs and reviewer workload.
Which comorbidity evidence can inform clinical discussions?
A traditional systematic review and meta-analysis assisted by LLMs is in the review stage.
Complete conventional synthesis, then use the case to evaluate mixed-information synthesis and individual applicability.
How much information can be retained when effect estimates are incomplete or measures and time windows differ?
Method boundaries and an evaluation design compare conventional and mixed-information synthesis for coverage and credibility.
Test additional information, statistical coherence and clinical value in the comorbidity review.
How should synthesised evidence fit decisions by patients, clinicians and institutions?
A decision-material evaluation design is established; comorbidity evidence will support further evaluation of individual applicability.
Evaluate applicability, traceability, justified abstention and decision quality; confidence alone is insufficient.
Which conclusions should change when new studies or corrections appear?
The programme includes update triggers, versioning and correction propagation.
Define change comparisons and review triggers; evaluate delay and maintenance costs.
How can unanswered clinical questions become the next study?
The plan connects gap detection, study design and research collaboration.
Select high-value gaps from existing reviews and assess topic selection and gap closure.
Can the full system improve workflow, decision quality and patient outcomes?
The plan compares human, human–AI and AI workflows in independent domains, then progresses toward hospital evaluation.
Progress through benchmarks, prospective silent testing, workflow pilots and outcome evaluation.
Can comorbidity, uncertainty and value trade-offs advance decision models?
A future foundational research programme builds on empirical synthesis and decision-translation studies.
Complete comorbidity and method evaluations before defining falsifiable model-research questions.
Compilation and governance research are established, with internal method evaluation in one review; comorbidity synthesis is underway.
Next: assess reuse across questions, errors and reviewer workload.
Compare conventional and mixed-information synthesis, including added information, individual applicability, justified abstention and decision quality.
Gate: complete a predefined independent comparative evaluation.
Study update triggers, correction propagation and human–AI collaboration through approved real-world evaluations.
Gate: evaluate traceability, update latency, safety escalation and accountability.
Study capability transfer and long-term health value, serving human health across more populations and care settings.
Gate: independent external validation, ongoing safety monitoring and applicable governance; expand use as evidence supports it.