bhklab.bsky.social

How Multimodal Datasets and Models Are Helping To Advance Cancer Care In the era of precision oncology, the integration of high-throughput, multimodal datasets presents both a formidable challenge and a transformative opportunity. We spoke to Dr. Benjamin Haibe-Kains ab...

In this feature with Technology Networks, @bhaibeka.bsky.social shares challenges working with clinical data, the impact of #LLMs and #agenticAI systems to scale curation. Special focus on spatially organized cancer cells aka 'ecotypes'.

Read more: www.technologynetworks.com/cancer-resea...

<em>Medical Physics</em> | AAPM Journal | Wiley Online Library Background Deep learning methods are promising in automating segmentation of organs at risk (OARs) in radiotherapy. However, the lack of a geometric indicator for dosimetry accuracy remains to be a .....

Excited to share our latest research published in American Association of Physicists in Medicine by Ruiyan Ni titled Geometrically focused training and evaluation of organs-at-risk segmentation via deep learning.

Full article - aapm.onlinelibrary.wiley.com/doi/10.1002/...

⛳ That’s a wrap on the #AIRCHECK Workshop 2025!

Researchers, data scientists & students gathered at Google Cloud Toronto to explore how AI/ML can accelerate drug discovery via aircheck.ai 💡

Huge shoutout to Shaghayegh Reza & Nabin Bagale for leading this! 👏👏

Exciting news! Great opportunity for the best and brightest postdoctoral researchers, early-career scientists, and established stars to UHN - www.surveymonkey.com/r/MYVQPM9
@uhnresearch.bsky.social

How should we analyze multi-metastatic tumors?

Most radiomics studies focus on single lesions, missing key inter-lesion differences. Our latest research evaluates 10 mathematical methods across 16,894 lesions and 3,930 patients.

🔗 Read more: [https://rdcu.be/ee54T]

🎉 Congratulations to Peter Her for receiving the prestigious Canadian Institutes of Health Research (CIHR) Doctoral Research Award for the project titled “Deciphering the pan-cancer functional landscape of circular RNAs in primary versus acquired resistance to immunotherapy for precision oncology”.

Generalizability of deep learning in organ-at-risk segmentation: A transfer learning study in cervical brachytherapy Accurate target and organs at risk (OARs) delineation is essential in radiation therapy (RT) treatment planning. However, manual delineation requires a considerable amount of radiation oncologists’ ti...

🎉 Congratulations Ruiyan Ni and team on their latest publication in the Radiotherapy and Oncology journal titled Generalizability of deep learning in organ-at-risk segmentation: A transfer learning study in cervical brachytherapy

Read more : www.thegreenjournal.com/article/S016...

Benjamin Haibe-Kains presented at the International Cancer Research Partnership Annual Meeting, showcasing the latest updates in PMATCH project titled “Streamlining Clinical Trial Criteria to Guide Precision Oncology.” Read more - lnkd.in/eNYWdiKv
#PMATCH

Congratulations to Katy Scott and Ruiyan Ni for getting accepted for oral presentations at
ICCR2024, the 20th International Conference on the use of Computers in Radiation Therapy.

Congratulations to Ian Smith, for successfully defending his thesis today. Your journey has been inspiring, and your expertise will undoubtedly make a significant impact in the field of pharmacogenomics!
Cheers to a new chapter filled with endless possibilities! 🥳🎉

Structural Genomics Consortium (SGC) Appoints Benjamin Haibe-Kains as Head of Data Science [Toronto, January 10, 2024] - Professor Benjamin Haibe-Kains has joined the Structural Genomics Consortium as the Head of Data Science to further support SGC’s ambition to generate high-quality and ...

Excited to announce that Dr. Benjamin Haibe Kains @bhaibeka.bsky.social has joined the Structural Genomics Consortium (SGC) as the Head of Data Science to further support SGC’s ambition to generate high-quality and reproducible data.
Read the press release here -

Cancer_RD_2023 Computational discovery pipelines for robust and translatable biomarkers of drug response https://www.med.uio.no/klinmed/english/research/projects/knep-norwegian-cancer-society-national-group-of-exper...

@bhaibeka.bsky.social presented exciting insights at Cancer R&D 2023, Boston, Massachusetts on:

🧬 Diving Deep into Drug Response Prediction Models
📊 Navigating the Noise in Biological Data
🔍Need for Clinical trial data to Validate AI models.

Thrilled to share this piece where @bhaibeka.bsky.social is interviewed by Medical Tribune! 🎬 He talks about the recent advances and the gaps in using AI for cancer biomarker discovery.
#esmo2023