How AI is Revolutionizing Cancer Research and Treatment? In this episode of the ZuriAI podcast, we explore how AI is transforming the prediction, diagnosis, and treatment of cancer. Artem Shmatko, a doctoral student and ML researcher at the German Cancer Research Center, explains AI’s growing influence in oncology.
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👉 Join the EngX: https://epa.ms/engx-club
How AI is Revolutionizing Cancer Research and Treatment? In this episode of the ZuriAI podcast, we explore how AI is transforming the prediction, diagnosis, and treatment of cancer. Artem Shmatko, a doctoral student and ML researcher at the German Cancer Research Center, explains AI’s growing influence in oncology.
We discuss:
What cancer is and why it’s challenging to prevent and diagnose
How AI is impacting drug discovery
Medical data aspects and limitations
The role of computer vision in histopathology
Challenges related to data management and patient privacy
NAVIGATION
0:00 Start
0:43 EngX
1:20 Meet our expert, Artem Shmatko
1:49 What is cancer? Complexity and diversity of cancers.
6:52 Why is it so difficult? Challenges of preventing cancer
10:17 How AI is becoming a pivotal tool in cancer prevention and treatment strategies.
12:40 MRI as a prevention technique.
14:38 The role of AI as a decision-support system in clinical settings.
22:01 AI in drug discovery. Transforming cancer treatment pipelines.
26:42 AI-powered recommendation systems for defining focus groups in clinical trials.
28:14 The complexities of data ingestion and collection in cancer research.
30:39 Handling patient-sensitive data: The ethical and technical challenges.
34:13 Certification and regulation in AI-driven oncology.
36:24 How computer vision and histopathology diagnostics are being redefined by AI.
38:27 The importance of image size and resolution in cancer diagnostics.
41:44 Discussing the potential of 100k*100k pixel resolution in medical imaging.
43:05 The technical limitations in cancer detection using computer vision.
46:03 Multiple instance learning
49:27 Data challenges in AI-driven oncology.
53:35 The role of open-source platforms in advancing medical AI.
57:26 Forecasting the impact of AI on the future of cancer prevention and diagnostics.
1:00:35 What industry challenges can AI overcome in oncology?
LINKS FROM THE EPISODE
🔹 AI's Evolution in Music/ ZuriAI #1: https://www.youtube.com/watch?v=KRJV-1Y61SM
🔹 What is cancer: https://www.cancer.gov/about-cancer/understanding/what-is-cancer
🔹 Classification of brain tumours: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8328013/
🔹 AI based solutions for determination of cell origin: https://www.nature.com/articles/s41586-021-03512-4
🔹 On diagnosing cancer using blood samples: https://doi.org/10.1093/nar/gkz942
🔹 Content-Based Image Retrieval (CBIR) for histological images: https://doi.org/10.1016/j.media.2020.101757
🔹 Automating drug discovery: https://doi.org/10.1038/nrd.2017.232
🔹AI for computational histopathology: https://www.nature.com/articles/s43018-022-00436-4
🔹 Pretrained feature extractors for Multiple Instance Learning (MIL) pipelines: https://www.nature.com/articles/s41591-024-02857-3
🔹 https://www.nature.com/articles/s41586-024-07441-w
🔹 Predicting DNA mutations from histological images: https://www.nature.com/articles/s43018-020-0085-8
WHERE TO WATCH US AND LISTEN
🔸 YouTube: https://youtu.be/XreqENCkpqE
🔸 Google Podcasts: https://bit.ly/awclub-en-google
🔸 Apple Podcasts: https://bit.ly/awclub-en-apple
🔸 Spotify: https://bit.ly/awclub-en-spotify
🔸 Download mp3: https://anywhereclub.simplecast.com/episodes/30
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