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The MÜNSTER UNIVERSITY HOSPITAL has issued a Procurement Plan/GPN/PIN notice for the procurement of a Speech Recognition for Medical and Nursing Staff in the Germany. This Procurement Plan/GPN/PIN notice was published on 13 Aug 2026 and is scheduled to close on 26 Aug 2026, with an estimated Procurement Plan/GPN/PIN value of Refer Document. Interested bidders can access detailed Procurement Plan/GPN/PIN information, eligibility criteria, and complete bidding documents by referencing TOT Ref No. 147142225, while the tender notice number is 560244-2026 and Registering on the platform.
Procurement Summary
Country: Germany
Summary: Speech Recognition for Medical and Nursing Staff
Deadline: 26 Aug 2026
Posting Date: 13 Aug 2026
Other Information
Notice Type: Procurement Plan/GPN/PIN
TOT Ref.No.: 147142225
Document Ref. No.: 560244-2026
Competition: ICB
Financier: Self Financed
Purchaser Ownership: Public
Tender Value: Refer Document
CPV Classification
48100000 - Industry specific software packagePurchaser's Detail
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Email: Login to see tender_detailsLogin to see details Tender Details Speech recognition for medical and nursing staff The University Hospital of Münster (UKM) needs a suitable speech recognition solution to support medical staff in creating medical documentation voice-assisted documentation. An appropriate solution is intended to support and simplify the creation of doctor's letters, diagnostic reports and other medical documents as well as the associated work processes. For this purpose First, an overview of the currently available technical solutions and approaches to voice-supported medical documentation will be obtained. The subject is solutions for speech recognition and voice-supported documentation that are suitable for use in... medical or clinical environment. Of particular interest are the possibilities for recording and processing spoken content as well as for creating and editing medical texts. The solutions should be able to take into account medical terminology and the terminology of different medical disciplines. In addition to classic speech recognition solutions, further technological approaches are also of interest in which spoken content for example, structured, summarized or used to support the creation of medical documents. In addition, the options for integrating the respective solutions into existing clinical... Documents
Document Type: Prior Information Notice Reference Number: GBBM20260812SY Contract Type: supplies Authority Type: cont-ent Doc Title: Speech recognition for medical and nursing staff Dispatch Date: 2026-08-12 Publish Date: 2026-08-13 Submission Date: 2026-08-26
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