Essec\Faculty\Model\Contribution {#2233
  #_index: "academ_contributions"
  #_id: "16086"
  #_source: array:26 [
    "id" => "16086"
    "slug" => "16086-machine-learning-in-healthcare-a-new-pattern-of-diffusion-for-general-purpose-technologies"
    "yearMonth" => "2025-11"
    "year" => "2025"
    "title" => "Machine learning in healthcare: a new pattern of diffusion for general purpose technologies"
    "description" => "AYOUBI, C. et FORAY, D. (2025). Machine learning in healthcare: a new pattern of diffusion for general purpose technologies. <i>Economics of Innovation and New Technology</i>, In press, pp. 1-32."
    "authors" => array:2 [
      0 => array:3 [
        "name" => "AYOUBI Charles"
        "bid" => "B00270671"
        "slug" => "ayoubi-charles"
      ]
      1 => array:1 [
        "name" => "Foray Dominique"
      ]
    ]
    "ouvrage" => ""
    "keywords" => array:5 [
      0 => "Healthcare"
      1 => "machine learning"
      2 => "general purpose technology"
      3 => "data appropriability"
      4 => "direction of technical change"
    ]
    "updatedAt" => "2026-01-09 10:20:48"
    "publicationUrl" => "https://doi.org/10.1080/10438599.2025.2584210"
    "publicationInfo" => array:3 [
      "pages" => "1-32"
      "volume" => "In press"
      "number" => ""
    ]
    "type" => array:2 [
      "fr" => "Articles"
      "en" => "Journal articles"
    ]
    "support_type" => array:2 [
      "fr" => "Revue scientifique"
      "en" => "Scientific journal"
    ]
    "countries" => array:2 [
      "fr" => null
      "en" => null
    ]
    "abstract" => array:2 [
      "fr" => "This paper examines the integration and impact of machine learning (ML) technologies in healthcare, recognized as a general-purpose technology (GPT). Leveraging an innovative search methodology, we analyse the progression of ML applications in healthcare through scientific publications and patents. We observe significant growth in research output, with publication rates quadrupling over the last decade. In contrast, patenting remains limited due to emerging business models that prioritize data accumulation over traditional patent-based approaches. The trends highlight two distinctive features in the diffusion of ML as a GPT in healthcare: first, the emergence of data as a novel appropriability mechanism offering competitive advantages to private innovators; and second, the unprecedented transformation of tech firms from mere technology suppliers to active service providers within the healthcare sector, giving rise to the emergence of a new pattern of ‘co-invention'. This new role of GPT producers becoming active players within the application sector is facilitated by tech companies’ extensive data analytics capabilities, creating new competitive advantages and strategic positioning in healthcare services. We then discuss the conditions and procedures that are likely to be necessary for a wider diffusion of ML applications within the healthcare sector."
      "en" => "This paper examines the integration and impact of machine learning (ML) technologies in healthcare, recognized as a general-purpose technology (GPT). Leveraging an innovative search methodology, we analyse the progression of ML applications in healthcare through scientific publications and patents. We observe significant growth in research output, with publication rates quadrupling over the last decade. In contrast, patenting remains limited due to emerging business models that prioritize data accumulation over traditional patent-based approaches. The trends highlight two distinctive features in the diffusion of ML as a GPT in healthcare: first, the emergence of data as a novel appropriability mechanism offering competitive advantages to private innovators; and second, the unprecedented transformation of tech firms from mere technology suppliers to active service providers within the healthcare sector, giving rise to the emergence of a new pattern of ‘co-invention'. This new role of GPT producers becoming active players within the application sector is facilitated by tech companies’ extensive data analytics capabilities, creating new competitive advantages and strategic positioning in healthcare services. We then discuss the conditions and procedures that are likely to be necessary for a wider diffusion of ML applications within the healthcare sector."
    ]
    "authors_fields" => array:2 [
      "fr" => "Management"
      "en" => "Management"
    ]
    "indexedAt" => "2026-01-30T10:21:41.000Z"
    "docTitle" => "Machine learning in healthcare: a new pattern of diffusion for general purpose technologies"
    "docSurtitle" => "Articles"
    "authorNames" => "<a href="/cv/ayoubi-charles">AYOUBI Charles</a>, Foray Dominique"
    "docDescription" => "<span class="document-property-authors">AYOUBI Charles, Foray Dominique</span><br><span class="document-property-authors_fields">Management</span> | <span class="document-property-year">2025</span>"
    "keywordList" => "<a href="#">Healthcare</a>, <a href="#">machine learning</a>, <a href="#">general purpose technology</a>, <a href="#">data appropriability</a>, <a href="#">direction of technical change</a>"
    "docPreview" => "<b>Machine learning in healthcare: a new pattern of diffusion for general purpose technologies</b><br><span>2025-11 | Articles </span>"
    "docType" => "research"
    "publicationLink" => "<a href="https://doi.org/10.1080/10438599.2025.2584210" target="_blank">Machine learning in healthcare: a new pattern of diffusion for general purpose technologies</a>"
  ]
  +lang: "fr"
  +"_score": 8.536525
  +"_ignored": array:2 [
    0 => "abstract.en.keyword"
    1 => "abstract.fr.keyword"
  ]
  +"parent": null
}