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AI/ML-Based Tumor Measurement & Analytics Engine

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State & Local

Contract Overview

Solicitation details, issuing organization, response deadlines, documents, and interested companies for this government contract opportunity.

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The contract seeks the development and validation of AI and machine learning tools designed to automate tumor measurement, segmentation, and treatment response assessment in oncology imaging, strictly aligned with RECIST and iRECIST clinical standards. The solution must include robust audit trails to ensure transparency, reproducibility, and compliance with regulatory expectations for medical imaging analytics. The system is intended to enhance accuracy and efficiency in longitudinal tumor tracking, reducing inter-observer variability and supporting clinical decision-making in cancer care. This subcontract opportunity is posted by UT Health San Antonio under NAICS code 541715 for research and development in the physical, engineering, and life sciences. The solicitation was posted on June 29, 2026, with a response deadline of August 7, 2026. The place of performance and agency office details are unspecified, but performance is expected to support clinical imaging workflows managed by the Texas-based organization. The contract aims to deliver a validated, clinically deployable AI engine with full documentation for use in oncology research and patient care settings.

General Info

Develop AI tools for tumor measurement and response assessment per RECIST/iRECIST standards with audit trails for oncology imaging.

Agency

Texas → Ut Health San AntonioView Agency

NAICS

541715 - Research and Development in the Physical, Engineering, and Life Sciences (except Nanotechnology and Biotechnology)View NAICS

Place of Performance

TX, USA

Set-Aside

NONE

Documents

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Organization & Contact Information

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AgencyTexas → Ut Health San Antonio
ContactsNo contacts available
OfficeN/A
Organization / Agency
Texas → Ut Health San Antonio
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Office AddressN/A
ContactsNo contact information available

Full Description

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Develop and validate AI-powered tools for automated tumor measurement, segmentation, and response assessment in oncology imaging per RECIST/iRECIST standards with audit trails.

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