{"entity":{"id":"foresight-ehr","kind":"technology","name":"Foresight (generative EHR model)","aka":[],"tldr":"A model trained on millions of hospital records that forecasts a patient's next diagnoses.","summary":"Foresight is a generative model of electronic health records from King's College London, an autoregressive transformer trained on sequences of coded clinical events so it can forecast a patient's next diagnoses in the way a language model predicts the next word. The Lancet Digital Health 2024 paper described the GPT-style model over coded EHR timelines, and Foresight 2 extended training to more than 5M patients. In oncology the use case is risk and trajectory forecasting, for instance flagging patients whose records suggest an undiagnosed cancer or a likely complication. Because it learns from coded data it inherits the biases and gaps of coding practice, and prospective evaluation of its forecasts changing care has not been reported. For a newcomer: Foresight reads a patient's record history and predicts what diagnoses might come next.","status":"emerging","asOf":"2026-09-08","links":[{"label":"Lancet Digital Health 2024","url":"https://doi.org/10.1016/S2589-7500(24)00025-6"}],"tags":["foundation-model","ehr"],"related":[],"cancers":[],"sections":["ai-computation"],"technologies":[],"targets":[],"drugs":[],"companies":[],"institutions":[],"pathways":[],"terms":[],"trials":[],"people":[],"bottlenecks":[],"keyPapers":["paper-kraljevic-lancet-digit-health"],"journals":[],"dependsOn":[],"notes":[],"principle":"Autoregressive transformer over clinical event sequences.","strengths":["Longitudinal reasoning"],"limitations":["Bias in coded data"],"since":2024},"route":"/technologies/foresight-ehr/","neighbours":{"section":[{"id":"ai-computation","kind":"section","name":"AI & Computation","route":"/fronts/ai-computation/"}],"paper":[{"id":"paper-kraljevic-lancet-digit-health","kind":"paper","name":"Foresight-a generative pretrained transformer for modelling of patient timelines using electronic health records: a retrospective modelling study","route":"/key-papers/paper-kraljevic-lancet-digit-health/"}],"roadmap":[{"id":"ai-oncology-roadmap","kind":"roadmap","name":"AI in oncology roadmap: pattern readers → foundation models → agents in the workflow","route":"/roadmaps/ai-oncology-roadmap/"},{"id":"ai-oncology-clinic","kind":"roadmap","name":"AI in the oncology clinic: from narrow cleared tools to multimodal decision support","route":"/roadmaps/ai-oncology-clinic/"}]}}