{"id":562557,"date":"2026-07-27T22:39:09","date_gmt":"2026-07-27T22:39:09","guid":{"rendered":"https:\/\/www.newsbeep.com\/il\/562557\/"},"modified":"2026-07-27T22:39:09","modified_gmt":"2026-07-27T22:39:09","slug":"ai-model-for-chest-ct-exams-from-hoppr","status":"publish","type":"post","link":"https:\/\/www.newsbeep.com\/il\/562557\/","title":{"rendered":"AI Model for Chest CT Exams from HOPPR"},"content":{"rendered":"

July 23, 2026\u00a0\u2014\u00a0HOPPR<\/a>\u00a0has\u00a0introduced HOPPR\u00a0EF Chest CT Narrative Model, a foundation model that processes 3D chest CT volumes and generates narrative language describing image characteristics across pulmonary, mediastinal, cardiac, upper abdominal, osseous, and soft tissue regions. The model is now available through HOPPR Forward Deployed Services, giving development teams expert support across every stage from evaluation to integration.\u00a0<\/p>\n

The HOPPR EF Chest CT Narrative Model was trained on a large proprietary dataset of chest CT studies from multiple clinical sites across the United States. A deliberate emphasis was placed on ensuring serious but less common conditions, including aortic injury, pulmonary embolism, rib fractures, and pneumothorax, are well represented in training. This approach reflects HOPPR\u2019s focus on building models that are useful across the realistic range of what clinicians encounter, not just the most routine cases.<\/p>\n

\u201cChest CT is one of the most information-dense studies in radiology. Getting AI to work well across everything it captures \u2014 the lungs, the heart, the aorta \u2014 is a genuinely hard problem, and we are pleased with what this model can do,\u201d said Khan Siddiqui, M.D., co-founder and CEO of HOPPR. \u201cBut the model is only part of what we are building. Our AI Foundry and Forward Deployed Services include secure infrastructure, curated data, and the clinical and technical expertise to help any organization move from a foundation model to a working application, regardless of where they are starting from. That is what makes this more than a model release.\u201d<\/p>\n

HOPPR Portfolio<\/p>\n

With this release, HOPPR\u2019s foundation model portfolio now spans three imaging modalities: chest X-ray, mammography and chest CT. The portfolio covers both AI-assisted classification and narrative-language-generation tasks.\u00a0 Models are available on the HOPPR\u00a0AI Foundry alongside third-party models from NVIDIA, Google, Microsoft, Stanford AIMI, and others. The Foundry also provides access to curated datasets and traceable development workflows, giving partners the data infrastructure and governance foundations that are difficult and expensive to build independently in a regulated healthcare environment.<\/p>\n

\u201cWorking with HOPPR\u2019s Forward Deployed Services team has allowed us to evaluate the Chest CT Narrative Model against our own data without needing to build that capability internally,\u201d said Kevin Kadakia, Chief Operating Officer at RadiologyOne. \u201cThe ability to adapt the model to our specific workflow and imaging environment is exactly what we were looking for in a foundation model partner.\u201d<\/p>\n

What distinguishes HOPPR is not just the models. Foundation models on the HOPPR AI Foundry are built on secure, HIPAA-ready infrastructure that is SOC 2 Type II and HITRUST e1 certified, and operates under a Quality Management System. Partners also have access to HOPPR Forward Deployed Services (FDS), a flexible engagement model that provides clinical workflow expertise, machine learning, fine-tuning, integration, and deployment support depending on what a team needs. Some partners need deep technical support to modify a model on their own data. Others need help navigating clinical workflow requirements or regulatory preparation. FDS meets them where they are, filling in the gaps that stand between a foundation model and a working application.<\/p>\n

To get started with the HOPPR\u00a0EF CT Chest Mammography Narrative Model,\u00a0click\u00a0here.<\/a>\u00a0\u00a0<\/p>\n

\u00a0<\/p>\n

\"HOPPR<\/p>\n","protected":false},"excerpt":{"rendered":"July 23, 2026\u00a0\u2014\u00a0HOPPR\u00a0has\u00a0introduced HOPPR\u00a0EF Chest CT Narrative Model, a foundation model that processes 3D chest CT volumes and…\n","protected":false},"author":2,"featured_media":562558,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[6],"tags":[85,46,125],"class_list":["post-562557","post","type-post","status-publish","format-standard","has-post-thumbnail","category-technology","tag-il","tag-israel","tag-technology"],"_links":{"self":[{"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/posts\/562557","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/comments?post=562557"}],"version-history":[{"count":0,"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/posts\/562557\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/media\/562558"}],"wp:attachment":[{"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/media?parent=562557"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/categories?post=562557"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/tags?post=562557"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}