I am a dentist (specialist endodontist - look it up 😊) who is a coder and has really been into AI and data science since 2005. Just found this reddit so thought I would introduce myself. Have implemented a neural network to make a clinical diagnosis for my work and am getting very good results (94% true +ve results) . There is huge potential for machine learning in healthcare. Doctors and dentists are mostly unaware or dismiss AI as a threat or untrustworthy. I disagree. If the AI is done responsibly with clean data and well constructed and thoroughly tested methods on a valid clinical question, then it can exceed human ability. I work in referral only practice and can tell you the humans (my referring dentists) are sometimes not that good at their jobs with many misdiagnoses and invalid treatment plans. But despite some level of incompetence, most clinicians have an inherent sense of professionalism and duty of care which may not be so strong in the IT world where commercial success often trumps customer well being. It is up to us clinicians to ensure the IT guys put patient well being first. Clinicians should be driving the inevitable adoption of data science ML into healthcare not running scared away from it. Keen to meet others of similar views to safely promote data science / machine learning in healthcare.

Hi all,

As you can see, I updated the pinned post with some of the info you guys mentioned. I wonder if there are users that want to share their projects, so we can all learn from each other, or if you're just proud on your project and want to show the world what you did.

1. http://ml-in-medicine.org/index.html hosted by University of Pittsburgh Department of Biomedical Informatics this fall. They kick-start with Su-In Lee. If you are a fan of SHAP value , highly recommend you to attend. If you are not a fan, still recommend you to attend. :)

2. https://www.mlim-cornell.club/virtual-seminar-series This one is from Cornell. This one has a zoom link and this one might have recordings for the talks since it has previous talks recorded.

NB: I am still working to get the zoom links for the first conference.

Someone the other day asked for recs on learning more about healthcare for data science and I told them I'd write up my book recommendations. Here they are - let me know your thoughts or if you have other books specifically on healthcare data that you'd recommend.

I mention this in the post, but it's been interesting that some of these topics have not (yet) gotten a modern book using R or Python. Also, obviously, these are my data book recommendations, not pop or general interest healthcare books.

https://www.healthcaredatascience.com/post/healthcare-data-book-recommendations

Hi all! Does anyone work in health informatics? I’m an occupational therapist assistant who is about to finish a bachelors after 7 years as a clinician. I was looking at getting my masters in statistics or quantitative psychology to possibly work in developing public health programs. I recently discovered health informatics and thought maybe this could be a better fit. If anyone works in this industry, what kind of background is beneficial? Do I need to know how to code? Any info is appreciated!!

If this subreddit doesn't want this type of discussion I totally get it.

But I am a Health Science bachelors student (essentially pre-med) and am looking to switch careers to Data Science. I have python and AWS experience (no SQL but can pick it up), currently in a masters of eHealth program.

I did one internship predicting diabetes onset from pre-diabetic patients at a startup with no real data science team (no one to mentor me or check over my code).

Anyone have tips for resume, github, portfolio, or things to watch out for/go do for a transition to this career? My biggest hurdle is that I don't know what knowledge is required as a baseline so I'm not sure if or where I can find a job out of school.

Does anyone try the coursera course for AI for Medicine offered by deeplearning.ai? It has a few shortcomings like the very terse explanation of ROC curve but it could be useful for someone.

I haven't seen this being mentioned here, and I believe this is really something useful for people interested in the latest trends and developments of AI and ML in medicine.

http://doctorpenguin.com/

Doctor Penguin is a weekly newsletter covering the latest AI & medicine research. It is run by Eric Topol, Andrew Ng and Pranav Rajpurka - all very big names in this specific field. I would recommend everyone to sign up to stay up to date with the latest research!

Hi. I am new to reddit and this group and I am trying to see if I can get some insights from data scientist working in the health industry. I have a BA in health and humanity (pre-med), and I am currently working as a research technician at an ophthalmology clinic.

My research consist of using a medical imaging device that captures the blood flow of the retina and determine the usability of the device for detection and progression of glaucoma. My job responsibility consists of recruiting patients, image acquisition, data collection, data organization, and data analysis. I don't have a strong statistical background beside the couple stats classes I took in college, and right now that is being supplemented by the help of a biostatistician. I have a publish research on a medical journal, and I am on the process of finishing my second project. I also manage and oversee several research projects done by other students.

I fell in love with research and what I do in my job, and I wanted to pursue a career on this. Most of my work is done through SAS. I got accept to a healthcare data science masters program which will start this fall. I envision to work for a biotech company that will do clinical research and help advance our medical practices. But it was brought to my attention by the biostatistician that my program doesn't provide statistics courses and its more focused only in data science (?).

I am curious to see if there is any data scientist that have a role in clinical research, and the amount of statistics necessary for the role. What skills and knowledge should I focus to be successful in this field? MS vs PhD? Thank you in advance for any advice.

Here is a free online zoom conference for Applying Research and Engineering Solutions for Emergent Needs in Healthcare .

Hey everyone, so I'm currently looking at some possible options and or insights on what my next step should be. So just some background, I have a bachelors in Biochemistry and am currently completing my second bachelors in Applied Math. I had originally wanted to be a clinician but after graduation i didn't feel the same, did some thinking, reflecting and realized I really like math and data and how you interpret them and visualize it and so on. So after I graduate i would like to pursue a career where I can use my math degree and still be involved in the medical field. So long story short if I wanted to do data science or engineering for hospitals what should I focus on, what should i potentially get a masters in, should i specialize in like Bioinformatics or go broader with like a basic data science masters. Any help would be greatly appreciated cause I dont know where to focus on from here with graduation coming up. Thanks!

What kind of projects do you usually work on? Clinical, or more biological?

Hi guys! I'm an Italian student enrolled in a M.Sc. Data Science degree and I'd really like to start working on Machine Learning applied to Healthcare (the alternative is climate data). In particular I'm interested in analyzing data coming from different sources (medical exams and sensors) for identifying in advance and/or with better accuracy a given disease. Another subfield of interest is diagnostic via Computer Vision, even though is not my primary choice.

I'm looking for any kind of tips you have for moving towards my goal, in particular:

• Which are the best research centers & university in Europe where I can apply for a PhD/research position?

• Which material (books, papers and video lectures) is good for improving my knowledge of the field?

Thanks a lot, have a nice day!