Taichung, Taiwan

China Medical University

China Medical University is listed as QS 2026 rank 509. China Medical University has 5 source-backed AI policy claim records from 3 official source attributions. The public record preserves original-language evidence snippets, source URLs, snapshot hashes, confidence, and review state.

Short answer

v1 public contract

China Medical University is listed as QS 2026 rank 509. China Medical University has 5 source-backed AI policy claim records from 3 official source attributions. The public record preserves original-language evidence snippets, source URLs, snapshot hashes, confidence, and review state.

Citation-ready summary

As of this public record, University AI Policy Tracker lists China Medical University as an agent-reviewed AI policy record last checked on May 17, 2026 and last changed on May 17, 2026. The record contains 5 source-backed claims, including 5 reviewed claims, from 3 official source attributions. Original-language evidence snippets and source URLs remain canonical, with public JSON available at https://eduaipolicy.org/api/public/v1/universities/china-medical-university.json. The entity-level confidence is 91%. This tracker is not legal advice, not academic integrity advice, and not an official university statement unless the linked source is the university's own official page.

Claim coverage5 reviewedSource languagezh-HantPublic JSON/api/public/v1/universities/china-medical-university.json

Policy signals in this record

  • Evidence includes Privacy claims.
  • Evidence includes Teaching claims.
  • Evidence includes Academic integrity claims.
  • Evidence includes Research claims.
  • Evidence includes Source status claims.
  • No specific AI service name is highlighted by the current public claim text.
  • Disclosure, acknowledgment, citation, or attribution language appears in the public claim text.
  • Teaching, assessment, coursework, or syllabus-related language appears in the public claim text.
Policy statusReviewed evidence-backed recordReview: Agent reviewedEvidence-backed claims5Reviewed5Candidate0Official sources3

This reference record summarizes visible public data only. Official sources and original-language evidence remain canonical; confidence is separate from review state.

This page is not legal advice, not academic integrity advice, and not an official university statement unless a linked source is the university's own official page.

Policy profile

Deterministic source-backed dimensions derived from this record's public claims.

Coverage score90/100Coverage labelbroad public coverageReview: Machine candidateAnalysis confidence76%

Policy profile rows are machine-candidate derived metadata. They are not final policy conclusions; inspect the linked claim evidence before reuse.

Analysis page-quality metadata is available at /api/public/v1/analysis/page-quality.json.

AI disclosure

China Medical University has 1 source-backed public claim for ai disclosure; deterministic analysis status: required.

RequiredMachine candidateConfidence75%Evidence1Sources1

Coursework

China Medical University has 1 source-backed public claim for coursework; deterministic analysis status: conditionally_allowed.

Conditionally AllowedMachine candidateConfidence77%Evidence1Sources1

Academic integrity

China Medical University has 1 source-backed public claim for academic integrity; deterministic analysis status: recommended.

RecommendedMachine candidateConfidence77%Evidence1Sources1

Approved tools

No source-backed public claim identifying approved or licensed AI tools is present in this profile.

The current public tracker record does not contain claim evidence that identifies institutionally approved, licensed, procured, or enterprise AI tools.

Not MentionedMachine candidateConfidence0%Evidence0Sources0

Named AI services

China Medical University has 1 source-backed public claim for named ai services; deterministic analysis status: recommended.

RecommendedMachine candidateConfidence77%Evidence1Sources1

Teaching guidance

China Medical University has 1 source-backed public claim for teaching guidance; deterministic analysis status: recommended.

RecommendedMachine candidateConfidence77%Evidence1Sources1

Security and procurement

No source-backed public claim about AI security review or procurement is present in this profile.

The current public tracker record does not contain claim evidence about security review, procurement, vendor approval, risk assessment, authentication, SSO, or enterprise licensing.

Not MentionedMachine candidateConfidence0%Evidence0Sources0

Coverage score measures breadth of public, source-backed coverage only. It is not a policy quality, strictness, legal adequacy, safety, or compliance score.

Evidence-backed claims

5 reviewed evidence-backed public claim

Privacy

China Medical University's Academic Affairs guidance cautions teachers and students to pay attention to privacy and information security and avoid entering personal or other people's private information into generative AI tools.

Review: Agent reviewedConfidence91%

Normalized value: avoid_private_information_in_genai_tools

Original evidence

Evidence 1
將「生成式AI」用於教學或學習時,師生應留意個人隱私與資訊安全,避免在「生成式AI」中輸入自己或他人之隱私資訊,以降低個人資訊外洩的風險。

Localized display only

When using generative AI for teaching or learning, teachers and students should pay attention to privacy and information security and avoid entering private information into generative AI.

Teaching

China Medical University's Academic Affairs generative AI teaching guidance asks instructors to communicate with students about course-specific ways and limits for using generative AI.

Review: Agent reviewedConfidence90%

Normalized value: instructor_course_ai_limits_guidance

Original evidence

Evidence 1
明確使用原則:教師應與學生溝通課程使用「生成式AI」的方式和限制,確定使用的範疇、場景和目的,以避免爭議。

Localized display only

Instructors are asked to communicate course-specific ways, limits, scope, scenarios, and purposes for using generative AI.

Academic Integrity

China Medical University's Academic Affairs guidance tells teachers and students to consider academic-ethics concerns before using generative AI and to avoid plagiarism and copyright violations in assignments, exams, and research papers.

Review: Agent reviewedConfidence90%

Normalized value: academic_integrity_caution_for_genai_use

Original evidence

Evidence 1
師生使用任何「生成式AI」工具前,應考量是否有違反學術倫理的疑慮。學術誠信是學習評量的基礎,所有作業、考試、研究論文必須遵守學倫理規範,勿抄襲,避免觸犯著作權法。

Localized display only

Teachers and students should consider academic-ethics concerns before using generative AI; assignments, exams, and research papers should follow academic ethics, avoid plagiarism, and avoid copyright violations.

Research

China Medical University's R&D reference guidance frames generative AI as a research-assistance tool and says researchers should verify AI-generated content, understand related policies, disclose use where required, and remain responsible for research outputs.

Review: Agent reviewedConfidence88%

Normalized value: research_genai_auxiliary_verification_disclosure_responsibility

Original evidence

Evidence 1
研究者在使用生成式AI時,應將其定位為輔助工具,切勿過度依賴或全然接受其產出的內容...研究者必須對AI生成的論述抱持審慎態度,務必親自查核相關資訊的正確性、可靠性與時效性。

Localized display only

Researchers are told to treat generative AI as an auxiliary tool rather than over-rely on its output, and to personally verify AI-generated content for correctness, reliability, and timeliness.

Source Status

Official China Medical University sources include public generative-AI guidance from Academic Affairs, Research and Development, and the Teacher Development Center; these sources support staged AI-policy extraction but should be read as guidance/context unless the source itself states a binding rule.

Review: Agent reviewedConfidence82%

Normalized value: official_genai_guidance_sources_found

Original evidence

Evidence 1
鼓勵教師將其視為精進教學的契機,因應新工具的發展適時調整課程規劃...並在應用AI 工具以提升教學成效的同時,確保學術誠信與法律合規性;學生端也應瞭解 AI 工具之使用限制。

Localized display only

The Teacher Development Center page frames AI as a teaching-development issue while emphasizing academic integrity, legal compliance, and student understanding of AI tool limitations.

Candidate claims

0 machine or needs-review claim

Candidate claims are not final policy conclusions. They preserve source URL, source snapshot hash, evidence, confidence, and review state so the record can be audited before review.

Official sources

3 source attribution

【重要宣導】中國醫藥大學 生成式人工智慧應用於學術研究之參考指引

cmurdc.cmu.edu.tw

Snapshot hash
f6be8ca5f4135be2f243b4e1a1218e0ba5fe7b4836bb170065b6ee86f731fafa

AI 學術倫理 | 中國醫藥大學教師發展中心

cmucfd.cmu.edu.tw

Snapshot hash
fe2f25bd899ccac6085a2d57c9174a9800c9a23afddf4e80e556e371b2024dcf

Change log

Source-check timeline and diff-style claim/evidence preview.

View the public change record for this university, including source snapshot hashes, claim review states, and a diff-style preview of current source-backed evidence.

Last checkedMay 17, 2026Last changedMay 17, 2026Open change log

Corrections and missing evidence

Corrections create review tasks and do not directly change this public record.

If an official source is missing, stale, moved, blocked, or incorrectly summarized, submit a source URL, policy change report, or institution correction for review. Corrections must preserve source URLs, source language, original evidence, review state, and audit history.

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