Hybrid Conferencee

International Conference on Medical Imaging and Machine Learning (ICMIML - 26)

4th - 5th November 2026 | Monrovia, Liberia

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Conference Notifications:

"Be sure to check this section regularly for all Research Plus International Conference updates. We’ll keep you informed about deadlines, event details, and more important notifications."

Call for Papers Extended:
"The deadline for full paper submissions has been extended for the Research Plus International Conference in Monrovia. Submit your research by today to participate in one of the top conferences."
Certificate of Presentation:
"Present your research and receive a Certificate of Presentation to recognise your valuable contribution to the conference."
Abstract Submissions Open:
"Abstract submissions for the Monrovia event are now open! Don’t miss the chance to present your research. Submit now."
Networking with Global Experts:
"Engage with researchers and professionals from around the world at the Monrovia conference. Build collaborations and gain insights from leading experts."
Keynote Speaker Sessions:
"Don’t miss our Keynote Sessions in Monrovia, featuring global leaders and innovators sharing their knowledge."
Best Paper & Best Paper Presentation Award:
"Submit your paper and stand a chance to win the Best Paper Presentation Award. The winner will be recognized at the conference in Monrovia."
SDG-Inspired Conference Focus:
"Our conference will highlight research that addresses global sustainability, inclusive education, and solutions for environmental challenges."

Call for Paper

The ICMIML aims to explore emerging trends and future directions in research and innovation. It provides a collaborative platform for researchers and professionals to share ideas that shape the future of their respective domains.

The conference highlights advancements in Machine Learning, encouraging innovative, solution-oriented research that addresses global challenges and technological evolution.

Authors are invited to submit papers addressing, but not limited to, the following areas:

01
Deep learning applications in medical imaging
02
Machine learning algorithms for disease diagnosis
03
Image segmentation techniques in healthcare
04
AI-driven predictive analytics in radiology
05
Ethical considerations in medical AI
06
Integration of imaging modalities with ML
07
Patient data privacy in machine learning
08
Real-time imaging analysis using AI
09
Novel feature extraction methods for imaging
10
Transfer learning in medical image classification
11
Automated detection of tumors using ML
12
Challenges in medical data annotation
13
Interpretable machine learning in healthcare
14
Comparative studies of imaging techniques
15
Impact of AI on radiologist workflows
16
Machine learning for personalized medicine
17
Data augmentation strategies for medical images
18
Clinical validation of machine learning models
19
Use of GANs in medical imaging
20
Future trends in medical imaging technology