Case Study Submission Deadline:	28 Feb 2026 (Tentative)
Notification of Acceptance:	Mid Mar 2026 (Tentative)

It is the submitter responsibility to ensure that all co-authors approve of the case study submission.

We are seeking case studies that demonstrate the integration of AI into clinical workflows for chest pain related management. The primary focus is on real-world applications, proven outcomes in improving diagnostic efficiency and accuracy, and support for clinical decision-making.

Topics of interest include, but are not limited to:

• AI-assisted ECG automatic analysis and critical value warning systems
• AI-assisted imaging recognition and diagnosis of acute critical conditions such as Acute Chest Pain, Aortic Dissection, and Pulmonary Embolism
• AI-based emergency triage and risk stratification prediction models

• A horizontally-displayed digital poster panel (either a 50” or 55” panel, randomly allocated) will be provided to display your poster.
• Submissions must ensure originality, clear focus, objective content, authentic data and MUST NOT contain any confidential information.
• Authors should type their initials and last name, but not degrees, titles, or institutional appointments. The name(s) of the institution(s) where the work was carried out should follow the list of authors and correspondingly indexed.
  e.g.: Wong TM(1), Chan NK(1)(2), Windsor CA(1)(2), Barclay TH(1)(2)
  (1)Department of Medicine & Therapeutics, Prince of Wales Hospital, (2)Accident and Emergency Medicine Academic Unit, The Chinese University of Hong Kong
• First word and all major words (nouns, verbs, adjectives, adverbs and pronouns) of the title should be capitalised, e.g. "Chest Pain Management in Elderly Patients in Hong Kong".
• Standard abbreviations should be used. Special or unusual abbreviation should be in parentheses after the term when it appears for the first time. Symbols should not be used.
• The e-poster MUST NOT contain any commercial logos or trademarks.
• You are recommended to organise your case study under the following headings for clarity:
  • Background and Objectives
  • Implementation and Methods
  • Results
  • Conclusion / Learning points
• The e-poster must adhere to the following specifications:
  • File format: JPG
  • Size in pixel: 3840 (w) x 2160 (h) – landscape orientation
  • Ensure high legibility with a minimum font size of 24pt for body text
  • Include text, diagram, figures and images only, do not add videos to your e-poster

Submission Platform:

• Abstracts must be submitted via the Submission System before the submission deadline. Late submissions will not be considered.

Please note that case studies submitted will be selected for poster display with reference to the following criteria:

• Relevance to AI application in chest pain management
• Originality/innovation
• Clinical and/or service enhancement

Shortlisted posters will be posted in the Congress designated exhibition area. Authors of accepted case studies are encouraged to attend the Congress to share insights and exchange ideas with the attending professionals.

Please note that case study may be rejected for exhibition if not conforming to the standard format. The Organising Committee reserves the right for the final editing of the case study.

The Case Study Submitter should warrant that all the information and content provided to CCPCC 2026 and the Hospital Authority does not infringe any third party rights including, but not limited to, intellectual property rights.

The Case Study Submitter grants the Hospital Authority a royalty-free, perpetual, irrevocable nonexclusive license to use, reproduce, publish, translate, distribute, and display the Content.