Biomedical Data Analysis Lab - BMD Lab

We are glad to share that our research work, "Equipping Computational Pathology Systems with Artifact Processing Pipelines: A Showcase for Computation and Performance Trade-offs", has been published in the BMC Journal of Medical Informatics and Decision Making.

This paper proposes a mixture of experts (MoE) scheme for detecting notable histological artifacts from whole slide images. We developed various end-to-end deep learning pipelines and evaluated them extensively on external cohorts for generalizability and robustness. The proposed artifact detection pipelines will not only ensure reliable CPATH predictions but may also provide quality control.

The source code, model weights, and dataset are made publicly available for computational pathology community to promote research in this area.

Link to the paper:
https://lnkd.in/deA2TxEh

Congratulations to all contributors: Neel Kanwal, Farbod Khoraminia, Umay Kiraz, Andrés David Mosquera Zamudio, Carlos Monteagudo, Emiel Janssen, Tahlita Zuiverloon, Chunming Rong and Kjersti Engan.

Congratulations to (Dr.) Mohsen Taheri Shalmani on successfully defending his PhD thesis, “Shape Statistics via Skeletal Structures”.
The BMD Lab is proud to celebrate this significant achievement and extends its warmest wishes for a bright and prosperous future ahead.

Congratulations to (Dr.) Neel Kanwal on successfully defending his PhD thesis, “Artifact Detection for Reliable Computational Pathology Systems using Artificial Intelligence”.
The BMD Lab is proud to celebrate this significant achievement and wishes for a bright future ahead.
Link to the thesis: https://uis.brage.unit.no/uis-xmlui/handle/11250/3131815

Congratulations to (Dr.) Liv Jorunn Høllesli on successfully defending her PhD thesis, “Stroke Mimics and In Depth Analysis of Computed Tomography Perfusion in Patients with Acute Ischemic Stroke”.

The BMD Lab is proud to celebrate this significant achievement and extends its warmest wishes for a bright and prosperous future ahead.

Congratulations to (Dr.) Saul Fuster Navarro on successfully defending his PhD thesis, “Deep Learning-Driven Diagnostic and Prognostic Solutions for Histopathological Images of Bladder Cancer”.
The BMD Lab is proud to celebrate this significant achievement and extends its warmest wishes for a bright and prosperous future ahead.

Our Ph.D. fellows Neel Kanwal and Saul Fuster Navarro presented their research results at the CLARIFY Final Conference, held in Valencia, Spain, from Jan 25-26, 2024. The conference held poster sessions to provide highlights for contributions made by BMD Lab members in the CLARIFY consortium.

Our Ph.D. fellow Jorge García-Torres Fernández presented his research work, titled "Comparative Analysis of Binary and Multiclass Activity Recognition in High-Quality Newborn Resuscitation Videos", at the Northern Lights Deep Learning (NLDL 2024) Conference, held during January 09-11, 2024 at Tromsø, Norway.

Link to the paper: https://lnkd.in/dp38pu78

Prof. Kjersti Engan gave a talk on "A Dual Convolutional Neural Network Pipeline for Melanoma Diagnostics and Prognostics" at the Northern Lights Deep Learning (NLDL 2024) Conference, held at Tromsø, Norway, during January 9-11, 2024. The conference also had poster sessions for presenting the latest research findings and fostering discussions among attendees.

Link to the preprint-version paper:https://arxiv.org/pdf/2312.08766.pdf

We are excited to share that our Ph.D. researcher Neel Kanwal published his article, "Are you sure it's an artifact? Artifact detection and uncertainty quantification in histological images" in Computerized Medical Imaging and Graphic Journal.
This research uses deep kernel learning models to detect histological artifacts and quantify uncertainty in prediction, providing improved accuracy from SOTA DCNN architectures. The proposed uncertainty-aware method can be integrated into the preprocessing pipeline of CPATH systems to provide reliable predictions and possibly serve as a quality control tool.

Check out the full article here: https://www.sciencedirect.com/science/article/pii/S0895611123001398

🌟 Exciting PhD Fellowship Opportunity in AI for Active and Assisted Living (AAL) at University of Stavanger!🌟

Are you passionate about Artificial Intelligence (AI) and its potential to improve the quality of life for older adults and people with special needs? We have an amazing opportunity for you! We are currently seeking talented individuals to join our prestigious fellowship program in AI for Active and Assisted Living.

📅 APPLICATION DEADLINE: February 7th, 2024

As a PhD Fellow in AI for AAL, you will have the chance to contribute to groundbreaking research aimed at developing innovative technologies and solutions that support active and independent living for the elderly. You will work closely with renowned experts in the field, benefiting from their mentorship and guidance throughout your journey.

💼 Key Responsibilities:

- Conducting cutting-edge research in AI for AAL

- Developing novel algorithms and models to support autonomous living for older adults

- Collaborating with interdisciplinary teams to integrate AI into smart homes and healthcare systems

- Publishing research findings in top-tier conferences and journals

📚 Qualifications:

- Master's degree (or nearing completion) in Computer Science, Artificial Intelligence, or relevant disciplines

- Prior experience or coursework related to AI, especially if you've worked on projects involving sensor (i.e., wearables or environmental) technology, healthcare applications, or data analytics in a healthcare context

- Strong programming skills (Python, C++, etc.)

- Solid understanding of machine learning and deep learning techniques

- Excellent problem-solving abilities and analytical thinking

- Good communication and teamwork skills

🎓 Benefits:

- Fully-funded PhD position for a duration of three years

- Access to state-of-the-art facilities and resources

- Opportunities to attend conferences and workshops

- Collaborations with international academic and industry partners

- Competitive salary package

✅ How to Apply:

Interested candidates are invited to visit our website and submit their applications through the following link:

https://www.jobbnorge.no/en/available-jobs/job/253478/phd-fellowship-in-ai-for-active-and-assited-living-aal

📢 Help us spread the word by sharing this amazing opportunity with your network! Feel free to tag potential candidates who might be interested in pursuing a PhD in AI for Active and Assisted Living. Together, let's shape the future of technology for the elderly and improve their lives!

https://lnkd.in/dVBVBFzr

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PhD Fellowship in AI for Active and Assited Living (AAL) (253478) | University of Stavanger Job title: PhD Fellowship in AI for Active and Assited Living (AAL) (253478), Employer: University of Stavanger, Deadline: Wednesday, February 7, 2024

Congratulations to (Dr.) Luca Tomasetti on successfully defending his PhD thesis, “Automatic AI-Driven segmentation of Acute Ischemic Stroke Regions with CP Perfusion Images”.
The BMD Lab is proud to celebrate this significant achievement with you and extends its warmest wishes for a bright and prosperous future ahead.

Our Ph.D. research fellow, Neel Kanwal, gave a lecture on his accepted research work, "Balancing Privacy and Progress in Artificial Intelligence: Anonymization in Histopathology for Biomedical Research and Education," at the International Conference on Frontiers of Artificial Intelligence, Ethics, and Multidisciplinary Applications (FAIEMA) Conference, held in Athens, Greece, on September 25th–26th, 2023. (https://www.faiema.org/)

Link to the preprint:https://arxiv.org/pdf/2307.09426.pdf