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New framework uses AI for patient-centered digital health outcomes

Researchers have introduced a new framework for patient-centered data science within the digital health sector. This framework utilizes a multidimensional model that integrates traditional clinical data with patient-reported outcomes, social determinants of health, and multi-omic data. By employing a multi-agent artificial intelligence approach, including large language models, the system aims to analyze complex datasets to optimize patient outcomes, mitigate bias, and enhance generalizability, ultimately fostering a learning healthcare system. AI

IMPACT This framework could enhance the translation of digital health innovations into clinical practice by improving AI-driven healthcare models.

RANK_REASON The item is an academic paper detailing a new framework and methodology. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

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New framework uses AI for patient-centered digital health outcomes

COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Mohsen Amoei, Dan Poenaru ·

    Patient-centered data science: an integrative framework for evaluating and predicting clinical outcomes in the digital health era

    arXiv:2408.02677v2 Announce Type: replace-cross Abstract: This study proposes a novel, integrative framework for patient-centered data science in the digital health era. We developed a multidimensional model that combines traditional clinical data with patient-reported outcomes, …