International Conference on Data Science Applications in Healthcare - (ICDSAH-26)


4th - 5th November, 2026 | Guangzhou, China

Multi-format (In-person/Virtual)

Registration Options

Explore conference registration categories designed for every mode of participation.

Important Dates

Pre-registration Deadline

5th October, 2026

Paper Submission Deadline

10th October, 2026

Last Date Of Registration

20th October, 2026

Date Of Conference

4th - 5th November, 2026

Downloads

Conference Session Tracks

SDG Wheel

Aligned with

UN Sustainable Development Goals

This conference contributes to global sustainability by aligning its research discussions and academic sessions with key United Nations Sustainable Development Goals. It fosters knowledge exchange, innovation, and collaborative engagement.

SDG 3 SDG 3 — Good Health and Well-being
SDG 4 SDG 4 — Quality Education
SDG 9 SDG 9 — Industry, Innovation and Infrastructure
SDG 16 SDG 16 — Peace, Justice and Strong Institutions
Explore

All Session Tracks

Track 01
Machine Learning Techniques in Healthcare

This track focuses on the application of machine learning algorithms in healthcare settings. It aims to explore innovative approaches to improve patient outcomes through predictive modeling and data-driven decision-making.

Track 02
Artificial Intelligence in Clinical Decision Support

This session will delve into the integration of artificial intelligence in clinical decision support systems. Participants will discuss the implications of AI technologies for enhancing diagnostic accuracy and treatment efficacy.

Track 03
Predictive Analytics for Patient Management

This track emphasizes the role of predictive analytics in managing patient care. It will cover methodologies for forecasting patient needs and optimizing resource allocation in healthcare facilities.

Track 04
Statistical Modeling in Biomedical Research

This session aims to highlight the importance of statistical modeling in biomedical research. It will address various modeling techniques used to analyze clinical data and derive meaningful insights.

Track 05
Big Data Challenges in Healthcare

This track will explore the challenges and opportunities presented by big data in the healthcare sector. Discussions will focus on data integration, privacy concerns, and the potential for improved health outcomes.

Track 06
Pattern Recognition in Medical Imaging

This session will investigate the application of pattern recognition techniques in medical imaging analysis. Participants will share advancements in image processing that enhance diagnostic capabilities.

Track 07
Bioinformatics Applications in Personalized Medicine

This track will focus on bioinformatics approaches that support personalized medicine initiatives. It will discuss how genomic data can be leveraged to tailor treatments to individual patients.

Track 08
Clinical Data Mining for Health Insights

This session will cover data mining techniques applied to clinical datasets for extracting actionable health insights. Participants will examine case studies demonstrating the impact of data mining on clinical practices.

Track 09
Ethical Considerations in Data Science for Healthcare

This track will address the ethical implications of using data science in healthcare. Discussions will include data privacy, informed consent, and the responsible use of AI and machine learning.

Track 10
Interdisciplinary Approaches to Healthcare Data Science

This session will highlight the importance of interdisciplinary collaboration in healthcare data science. It will showcase how diverse fields contribute to innovative solutions in health data analytics.

Track 11
Emerging Trends in Healthcare Data Analytics

This track will explore the latest trends and technologies in healthcare data analytics. Participants will discuss future directions and the potential impact of these trends on healthcare delivery.