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Ask HN: What medical datasets do you need?

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Re: Ask HN: What medical datasets do you need?

#83
For those interested in global health, we've tried to collate as much data as possible at http://ghdx.healthdata.org/ (disclosure: I'm the director of data science at IHME, which hosts this).

Note that most of this data is population level epidemiologic and administrative stuff, not the detailed biomedical measurements I see most people requesting - but I promise you there's some really interesting things that can be done with it nonetheless!

Re: Ask HN: What medical datasets do you need?

#84

OP: You need more doctor data. Given you have surgeon [x] what are odds of a successful surgery with [x]. THIS is the guarded secret -- yet the most valuable. If you have medical data (or want to be a cofounder) please email me :ransom1538 at gmail.com -- a prototype: https://www.opendoctor.io to find out data to this very question.

In the UK, under the NHS, summary data regarding a surgeons performance is published [1].

There is an interesting debate about whether this is a good thing or not. One argument is that it improves transparency and allows patients to make a better, more informed choice of who operates on them.

The counterargument is that most patients don't understand that there is an element of probability distribution involved. Perhaps more importantly, if the thought process of a surgeon changes from "performing surgeries to the best of my abilities and knowing I will lose my job if I am dangerous" to "all my results are published for public scrutiny so I need to have a survival rate as close to 100% as possible as that is all the public comprehend" may lead to surgeons only being willing to take on cases which are very likely to be successful, as taking a difficult or last-chance case will have a high probability of mortality and therefore will affect their numbers. This would be a loss for many people. I don't know if any research has been done to determine whether that has borne out or not though.

[1] https://www.nhs.uk/service-search/Consultants/performanceind...

Re: Ask HN: What medical datasets do you need?

#86

Dermatology, eye conditions, blood cells, tissue, viruses, urine, saliva, everything that can allow an app to give you a first diagnose before heading to the doctor. I foresee in less than ten years we will have a doctor in our pockets. No, it won't cure us and it won't replace a doctor, but it will give us all the information we need to have a 99% certainty of our condition. -- Second batch for animals and their con…

> Second batch for animals and their conditions.

We can learn a lot from animals, and clearly the data should not be protected as much as for humans. Therefore, I'm wondering, where is all the animal data? Could we already start to build models using that data? This could be useful for researching conditions that are more difficult to get data for in the case of humans.

Re: Ask HN: What medical datasets do you need?

#87
I'm wondering how an automated diagnosis could work in practice.

The data probably contains a number of symptoms or measurements (bloodwork), and a diagnosis by a doctor.

I can see how you can train a deep-learning model for that.

What if the patient is prescribed medication. Is the condition of the patient over time (after giving the medication) tracked by doctors?

Personally, I have found that once a doctor prescribes me some medication, he never asks me how things are going (except maybe once). So how accurate can the data be?

Re: Ask HN: What medical datasets do you need?

#89
FYI, as far as I know, the Harvard Personal Genome Project is one of the only publicly available resources that has whole genome (and other) data along with health record information available for free use (CC0 licensed) [1]. Open Humans [2] and OpenSNP [3] have data along with various degrees of health record and phenotype information as well.

[1] http://www.personalgenomes.org/

[2] https://www.openhumans.org/

[3] https://opensnp.org/

Re: Ask HN: What medical datasets do you need?

#90

So, the last startup I was a fulltime engineer at actually worked in this area. What I would suggest to be maximally useful would be to focus on physiological data: EKG/ECG, EMG, glucose, SPO2, maybe various blood work counts. All of those are data that are both well-understood and are thrown away regularly, and that if fed into a computer with modern ML methods we could maybe see some really cool stuff. I'd suggest…

Curious why you say stay away from the billing codes and EHR side? That is one area I'm looking at that is ripe for AI and deep learning to optimize.
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