+1 7178835943 [email protected]
Hybrid Event (In-person or Virtual participation)

International Conference on AI and Data Science for Healthcare Informatics · Registering as Listener

ICADSHI
📅 28 – 29 Jun 2027 📍 Malmo Municipality, Sweden 👥 Standard / Physical Participation
Listener Registration From
$185
Registration Benefits:
Official invitation letterIssued automatically after registration
🎖 Certificate & digital materialsGet certificate, slides and resource materials
🌐 Supporting global researchConnect with researchers across 30+ countries

Select registration mode

Prices are shown before tax and bank charges — no surprises at checkout.

All sessions Networking Certificate Invitation letter Conference kit

Your details

We only need what's required to register and email your confirmation. Everything else is optional.

Coupon Code (If Any)

Have a code? Apply it here — the discount updates the total immediately.

🏷

For Support Please Contact

VISAMASTERCARDNET BANKINGUPI

Payments encrypted & processed securely. Refundable up to 14 days before the event.

Registration summary

ConferenceInternational Conference on AI and Data Science for Healthcare Informatics
ModeStandard / Physical
ParticipationListener
Registration fee$185.00
Bank charges (5.8%)$10.73
Total payable $195.73

Includes all bank processing charges — the amount above is exactly what will be charged.

Need help?

Contact our registration team:

📞 +91 93445 35349

Benefits of Registering as Listener

👥Access to Conference Sessions
🔗Networking Opportunities
🎖Certificate of Participation
Invitation Letter Support
📚Conference Kit / Materials
🎤Access to Keynote Sessions
• Conference Session Tracks •
SDG

SDG-Aligned Research Themes

Conference tracks support global knowledge exchange, innovation, and sustainable development priorities across diverse disciplines.

SDG 3 SDG 4 SDG 9 SDG 16

This track focuses on the development and implementation of AI technologies in clinical decision support systems. It aims to explore how these systems can enhance diagnostic accuracy and improve patient outcomes.

This session will delve into the application of predictive analytics in healthcare settings, emphasizing the use of machine learning algorithms to forecast patient outcomes. Participants will discuss methodologies for integrating predictive models into clinical workflows.

This track examines innovative approaches to analyzing patient records using data science techniques. The focus will be on improving data management practices and enhancing the quality of patient care through informed decision-making.

This session addresses the role of AI and data science in disease surveillance and public health informatics. Discussions will center on the development of systems that can detect and respond to health threats in real-time.

This track highlights the integration of AI in medical imaging, focusing on techniques that enhance image analysis and interpretation. Participants will explore the impact of these advancements on diagnostic processes and treatment planning.

This session will cover the application of data science and AI in the drug discovery process. Emphasis will be placed on computational methods that streamline the identification and development of new therapeutic agents.

This track explores methodologies for integrating diverse biomedical data sources to facilitate comprehensive analysis. The aim is to enhance research outcomes and clinical applications through improved data interoperability.

This session focuses on the challenges and opportunities presented by big data in healthcare. Discussions will include analytical techniques that can harness large datasets to drive insights and inform policy decisions.

This track investigates the intersection of personalized medicine and artificial intelligence. Participants will discuss how AI can tailor treatment plans to individual patient profiles, improving therapeutic efficacy.

This session will explore the latest innovations in health IT and their implications for healthcare delivery. Emphasis will be placed on successful implementation strategies that enhance system usability and patient engagement.

This track examines the role of analytics in optimizing hospital management practices. Discussions will focus on data-driven strategies that improve operational efficiency and patient satisfaction in healthcare facilities.

COPYRIGHT © 2026 ISAR. ALL RIGHTS RESERVED