Using Crowd Sourcing for Early Detection of Cancer

This week, I have been at the Nvidia GPU Technology Conference.  I have seen some fantastic talks by some world renown researchers - Daniel Rubin, MD, from Stanford University who is working on Quantitative Medical Imaging to find tumors using AI and Machine Learning; Dexter Hadley, MD/PhD, from the University of Central Florida School of Medicine who is working on translating big data into precision medicine and digital health, particularly for breast cancer, using AI and Machine Learning.  While they showed their amazing work, they both stressed the same thing - WE NEED MORE DATA.  This is truly the struggle of AI and big data.  Just like our brains, the neural network can only learn what it is trained on.  The more training data, the better the predictions the model can make. What does this mean?  The more training data, the better the model is at detecting breast cancer, coronary artery disease, and other medical conditions.  This makes medicine more precise and patient care better.

How do we get more data?  X-rays, MRI scans, PET scans must be shared with these groups that are doing the Deep Learning/Artificial Intelligence work.  Interestingly, patients don't own their data - the hospitals do.  In order for patients to get their data to researchers, they must sign releases to get the data sent.  Are we willing to share this data?  I think we have to.  Sharing my data can help researchers improve their AI models, thereby making medicine more precise and saving lives. 

Here is one great example.  Dr. Hadley mentioned a website, www.breastwecan.com, a crowd sourcing initiative that is empowering patients to share their imaging and electronic health records.  Check it out.  Are you willing to share your data to help medicine get better and possibly save other lives?  I think this is a great initiative.

For more information on researchers who are using AI to save lives, see the websites below:

Dr. Dexter Hadley - www.hadleylab.org/
Dr. Daniel Rubin - rubinlab.stanford.edu/

If you have questions and want to connect, you can message me on LinkedIn or Twitter. Also, follow me on Twitter @pacejohn and LinkedIn https://www.linkedin.com/in/john-pace-phd-20b87070/

#artificialintelligence #AI #machinelearning #stanford #ucf #rubinlab #hadleylab #medicalimaging #nvidia #gpu #gtc #breastwecan #computervision #cancer #breastcancer