Hi!
EHF Director of Public Health and Longevity Programs Daria Khaltourina:
About EHF's value
Watch the video:
https://youtu.be/A0s5a01hpN0
Topic: [ANN][ICO] EHF eHealth First - page 335. (Read 97848 times)
It happens quite often, that a doctor made a wrong diagnosis, because he didn't see the very rare tropical disease f.e..
Computer can make suggestions, so that the doctor don't overlook such rare diseases.
But also because of the very strong psychologic component of the most diseases (psychosomatic) a doctor, which will listen to you, will always have the basic place as a human in this business.
Computer can make suggestions, so that the doctor don't overlook such rare diseases.
But also because of the very strong psychologic component of the most diseases (psychosomatic) a doctor, which will listen to you, will always have the basic place as a human in this business.
That's a really interesting point you bring up there.
Many afflictions aren't physical but mental. In the white paper they only talk about mental health in a legal way. It's harder to diagnose because the data from the patient can be affected by their mental state.
It is definitely possible for a machine learning algo to match sets of symptoms with a diagnosis. The problem is at the patient level, the patient often cannot describe their symptoms accurately (especially in mental issues). In terms of information, garbage-in equals garbage-out.
Not at the beginning, but yes it could, one way or another AI will help A LOT the app, and the diagnose made in general, and because the AI learn constantly with every patient that uses it, it will learn very FAST.
We are slowly moving towards a world where AI will have much more to say then we can ever imagine.. AI doesn't sleep and doesn't make human errors.
But there are something that AI can't do especially to diagnose psicology aspect. This will need human's touch. But, yes, AI will help a lot in another aspects.
The concept of EHF is very good, but I think it’s a long term project. The potential is huge but the project will need time to develop more the concept and make some partnerships I think.
You think it's a long term project?well.. that should have been clear from the start, looking at the roadmap
)many people are expecting a project to deliver the goods in a year or so. this one will take a long time cause it's such a complex endevour.
Most crypto projects are still in beta or not even that. Even whitepapers can reach a billion dollar market cap. eHealth is honest about the long roadmap. That could pay off in the end.
That's why this market is fucked up! Just look at Tron
wasn't Tron a classic pump and dump? I feel bad for the people who bought that stuff. still EHF is putting their cards on the table and saying , this is gonna take a while. you gotta respect that.
Tron is still in the top of crypto. for no reason. EHF on the other hand is a proper project and doesn't make empty promises, but honestly says it takes time to deliver a decent project - which it does!
That is why people may start investing here next year because is too long to keep money here paralyze without moving, so this is for the patient, even, due to its long-term goal, it may just go below ICO price.
I see where you are coming from but you might not be that accurate about the investment being stuck. At the end of the ICO around Aug, you will be getting the tokens. Even if they are traded below ICO price you would've made enough profit with the bonus tokens which can be traded at etherdelta or forkdelta. And when it get listed in December at exchanges, as per the roadmap, it should be up and running. The only thing that looks long term is the project fulfillment which even coins like verge are still working on even though the nature of the project is different.
The concept of EHF is very good, but I think it’s a long term project. The potential is huge but the project will need time to develop more the concept and make some partnerships I think.
You think it's a long term project?well.. that should have been clear from the start, looking at the roadmap
)many people are expecting a project to deliver the goods in a year or so. this one will take a long time cause it's such a complex endevour.
Most crypto projects are still in beta or not even that. Even whitepapers can reach a billion dollar market cap. eHealth is honest about the long roadmap. That could pay off in the end.
That's why this market is fucked up! Just look at Tron
wasn't Tron a classic pump and dump? I feel bad for the people who bought that stuff. still EHF is putting their cards on the table and saying , this is gonna take a while. you gotta respect that.
Tron is still in the top of crypto. for no reason. EHF on the other hand is a proper project and doesn't make empty promises, but honestly says it takes time to deliver a decent project - which it does!
That is why people may start investing here next year because is too long to keep money here paralyze without moving, so this is for the patient, even, due to its long-term goal, it may just go below ICO price.
The concept of EHF is very good, but I think it’s a long term project. The potential is huge but the project will need time to develop more the concept and make some partnerships I think.
You think it's a long term project?well.. that should have been clear from the start, looking at the roadmap
)many people are expecting a project to deliver the goods in a year or so. this one will take a long time cause it's such a complex endevour.
Most crypto projects are still in beta or not even that. Even whitepapers can reach a billion dollar market cap. eHealth is honest about the long roadmap. That could pay off in the end.
That's why this market is fucked up! Just look at Tron
wasn't Tron a classic pump and dump? I feel bad for the people who bought that stuff. still EHF is putting their cards on the table and saying , this is gonna take a while. you gotta respect that.
Tron is still in the top of crypto. for no reason. EHF on the other hand is a proper project and doesn't make empty promises, but honestly says it takes time to deliver a decent project - which it does!
It happens quite often, that a doctor made a wrong diagnosis, because he didn't see the very rare tropical disease f.e..
Computer can make suggestions, so that the doctor don't overlook such rare diseases.
But also because of the very strong psychologic component of the most diseases (psychosomatic) a doctor, which will listen to you, will always have the basic place as a human in this business.
Computer can make suggestions, so that the doctor don't overlook such rare diseases.
But also because of the very strong psychologic component of the most diseases (psychosomatic) a doctor, which will listen to you, will always have the basic place as a human in this business.
That's a really interesting point you bring up there.
Many afflictions aren't physical but mental. In the white paper they only talk about mental health in a legal way. It's harder to diagnose because the data from the patient can be affected by their mental state.
It is definitely possible for a machine learning algo to match sets of symptoms with a diagnosis. The problem is at the patient level, the patient often cannot describe their symptoms accurately (especially in mental issues). In terms of information, garbage-in equals garbage-out.
Not at the beginning, but yes it could, one way or another AI will help A LOT the app, and the diagnose made in general, and because the AI learn constantly with every patient that uses it, it will learn very FAST.
We are slowly moving towards a world where AI will have much more to say then we can ever imagine.. AI doesn't sleep and doesn't make human errors.
While we are looking for the holy grail of accurate diagnosis in medical field, we must be mindful that human element is important for fast and accurate decision making like the doctors do. AI and machine learning can only add to the human touch of a doctor but if you substitute it, it is bound to fail because machines, despite our ardent belief in it, do make mistakes due to hardware failure or software bug...and that's why you still see doctors around the world using their manual pump Blood Pressure monitor instead of the dully digital one. I look forward to EHealth taking up in this endeavour.
It happens quite often, that a doctor made a wrong diagnosis, because he didn't see the very rare tropical disease f.e..
Computer can make suggestions, so that the doctor don't overlook such rare diseases.
But also because of the very strong psychologic component of the most diseases (psychosomatic) a doctor, which will listen to you, will always have the basic place as a human in this business.
Computer can make suggestions, so that the doctor don't overlook such rare diseases.
But also because of the very strong psychologic component of the most diseases (psychosomatic) a doctor, which will listen to you, will always have the basic place as a human in this business.
That's a really interesting point you bring up there.
Many afflictions aren't physical but mental. In the white paper they only talk about mental health in a legal way. It's harder to diagnose because the data from the patient can be affected by their mental state.
It is definitely possible for a machine learning algo to match sets of symptoms with a diagnosis. The problem is at the patient level, the patient often cannot describe their symptoms accurately (especially in mental issues). In terms of information, garbage-in equals garbage-out.
Not at the beginning, but yes it could, one way or another AI will help A LOT the app, and the diagnose made in general, and because the AI learn constantly with every patient that uses it, it will learn very FAST.
We are slowly moving towards a world where AI will have much more to say then we can ever imagine.. AI doesn't sleep and doesn't make human errors.
It happens quite often, that a doctor made a wrong diagnosis, because he didn't see the very rare tropical disease f.e..
Computer can make suggestions, so that the doctor don't overlook such rare diseases.
But also because of the very strong psychologic component of the most diseases (psychosomatic) a doctor, which will listen to you, will always have the basic place as a human in this business.
Computer can make suggestions, so that the doctor don't overlook such rare diseases.
But also because of the very strong psychologic component of the most diseases (psychosomatic) a doctor, which will listen to you, will always have the basic place as a human in this business.
That's a really interesting point you bring up there.
Many afflictions aren't physical but mental. In the white paper they only talk about mental health in a legal way. It's harder to diagnose because the data from the patient can be affected by their mental state.
It is definitely possible for a machine learning algo to match sets of symptoms with a diagnosis. The problem is at the patient level, the patient often cannot describe their symptoms accurately (especially in mental issues). In terms of information, garbage-in equals garbage-out.
Not at the beginning, but yes it could, one way or another AI will help A LOT the app, and the diagnose made in general, and because the AI learn constantly with every patient that uses it, it will learn very FAST.
It happens quite often, that a doctor made a wrong diagnosis, because he didn't see the very rare tropical disease f.e..
Computer can make suggestions, so that the doctor don't overlook such rare diseases.
But also because of the very strong psychologic component of the most diseases (psychosomatic) a doctor, which will listen to you, will always have the basic place as a human in this business.
Computer can make suggestions, so that the doctor don't overlook such rare diseases.
But also because of the very strong psychologic component of the most diseases (psychosomatic) a doctor, which will listen to you, will always have the basic place as a human in this business.
That's a really interesting point you bring up there.
Many afflictions aren't physical but mental. In the white paper they only talk about mental health in a legal way. It's harder to diagnose because the data from the patient can be affected by their mental state.
It is definitely possible for a machine learning algo to match sets of symptoms with a diagnosis. The problem is at the patient level, the patient often cannot describe their symptoms accurately (especially in mental issues). In terms of information, garbage-in equals garbage-out.
Not at the beginning, but yes it could, one way or another AI will help A LOT the app, and the diagnose made in general, and because the AI learn constantly with every patient that uses it, it will learn very FAST.
It happens quite often, that a doctor made a wrong diagnosis, because he didn't see the very rare tropical disease f.e..
Computer can make suggestions, so that the doctor don't overlook such rare diseases.
But also because of the very strong psychologic component of the most diseases (psychosomatic) a doctor, which will listen to you, will always have the basic place as a human in this business.
Computer can make suggestions, so that the doctor don't overlook such rare diseases.
But also because of the very strong psychologic component of the most diseases (psychosomatic) a doctor, which will listen to you, will always have the basic place as a human in this business.
That's a really interesting point you bring up there.
Many afflictions aren't physical but mental. In the white paper they only talk about mental health in a legal way. It's harder to diagnose because the data from the patient can be affected by their mental state.
It is definitely possible for a machine learning algo to match sets of symptoms with a diagnosis. The problem is at the patient level, the patient often cannot describe their symptoms accurately (especially in mental issues). In terms of information, garbage-in equals garbage-out.
It happens quite often, that a doctor made a wrong diagnosis, because he didn't see the very rare tropical disease f.e..
Computer can make suggestions, so that the doctor don't overlook such rare diseases.
But also because of the very strong psychologic component of the most diseases (psychosomatic) a doctor, which will listen to you, will always have the basic place as a human in this business.
Computer can make suggestions, so that the doctor don't overlook such rare diseases.
But also because of the very strong psychologic component of the most diseases (psychosomatic) a doctor, which will listen to you, will always have the basic place as a human in this business.
That's a really interesting point you bring up there.
Many afflictions aren't physical but mental. In the white paper they only talk about mental health in a legal way. It's harder to diagnose because the data from the patient can be affected by their mental state.
It is definitely possible for a machine learning algo to match sets of symptoms with a diagnosis. The problem is at the patient level, the patient often cannot describe their symptoms accurately (especially in mental issues). In terms of information, garbage-in equals garbage-out.
I think in a couple years we can more easily measure a lot of aspects. Mental issues might be deduced by simply giving the subject tasks and seeing how they perform. But yeah, mental disorders are a whole other ballgame.
It happens quite often, that a doctor made a wrong diagnosis, because he didn't see the very rare tropical disease f.e..
Computer can make suggestions, so that the doctor don't overlook such rare diseases.
But also because of the very strong psychologic component of the most diseases (psychosomatic) a doctor, which will listen to you, will always have the basic place as a human in this business.
Computer can make suggestions, so that the doctor don't overlook such rare diseases.
But also because of the very strong psychologic component of the most diseases (psychosomatic) a doctor, which will listen to you, will always have the basic place as a human in this business.
That's a really interesting point you bring up there.
Many afflictions aren't physical but mental. In the white paper they only talk about mental health in a legal way. It's harder to diagnose because the data from the patient can be affected by their mental state.
It is definitely possible for a machine learning algo to match sets of symptoms with a diagnosis. The problem is at the patient level, the patient often cannot describe their symptoms accurately (especially in mental issues). In terms of information, garbage-in equals garbage-out.
It happens quite often, that a doctor made a wrong diagnosis, because he didn't see the very rare tropical disease f.e..
Computer can make suggestions, so that the doctor don't overlook such rare diseases.
But also because of the very strong psychologic component of the most diseases (psychosomatic) a doctor, which will listen to you, will always have the basic place as a human in this business.
Computer can make suggestions, so that the doctor don't overlook such rare diseases.
But also because of the very strong psychologic component of the most diseases (psychosomatic) a doctor, which will listen to you, will always have the basic place as a human in this business.
That's a really interesting point you bring up there.
Many afflictions aren't physical but mental. In the white paper they only talk about mental health in a legal way. It's harder to diagnose because the data from the patient can be affected by their mental state.
It would be cool if we could hear a bit about private investors, how many joined and what kind of investors these are
Maybe Vitalik Buterin is investing in eHealth too? Who knows
Maybe Vitalik Buterin is investing in eHealth too? Who knows
The existence of private investors should be notified to the public to maintain openness. Maybe they'll tell us later.
Hold on there a bit longer, the end of the private sale is close, I'm sure they gonna disclose some information after it ends. Hope for some big news.
I hope as well they got on board some big investors who can see the value in this project and the team.
It would be very good if he would make public the big private investors.But there is the possibility that some of them will not give the promise to make them public.
I think the project would gain more credibility and I think many will be willing to invest.
It would be cool if we could hear a bit about private investors, how many joined and what kind of investors these are
Maybe Vitalik Buterin is investing in eHealth too? Who knows
Maybe Vitalik Buterin is investing in eHealth too? Who knows
The existence of private investors should be notified to the public to maintain openness. Maybe they'll tell us later.
Hold on there a bit longer, the end of the private sale is close, I'm sure they gonna disclose some information after it ends. Hope for some big news.
I hope as well they got on board some big investors who can see the value in this project and the team.
It would be cool if we could hear a bit about private investors, how many joined and what kind of investors these are
Maybe Vitalik Buterin is investing in eHealth too? Who knows
Maybe Vitalik Buterin is investing in eHealth too? Who knows
The existence of private investors should be notified to the public to maintain openness. Maybe they'll tell us later.
Hold on there a bit longer, the end of the private sale is close, I'm sure they gonna disclose some information after it ends. Hope for some big news.
I hope as well they got on board some big investors who can see the value in this project and the team.
It would be cool if we could hear a bit about private investors, how many joined and what kind of investors these are
Maybe Vitalik Buterin is investing in eHealth too? Who knows
Maybe Vitalik Buterin is investing in eHealth too? Who knows
The existence of private investors should be notified to the public to maintain openness. Maybe they'll tell us later.
Hold on there a bit longer, the end of the private sale is close, I'm sure they gonna disclose some information after it ends. Hope for some big news.
I hope as well they got on board some big investors who can see the value in this project and the team.
I agree with you, i know in this phase usually caps are more higher than the other phases, 2 eth is high for at this moment but taking communities attention with lower caps is more important(imo).
The concept of EHF is very good, but I think it’s a long term project. The potential is huge but the project will need time to develop more the concept and make some partnerships I think.
You think it's a long term project?well.. that should have been clear from the start, looking at the roadmap
)many people are expecting a project to deliver the goods in a year or so. this one will take a long time cause it's such a complex endevour.
Most crypto projects are still in beta or not even that. Even whitepapers can reach a billion dollar market cap. eHealth is honest about the long roadmap. That could pay off in the end.
Most importantly i think they have been able to define what real problems they are going to solve and how.
Sometimes good idea can stay on paper so Hopefully ehealth wont be like them.
I will hope that only ph value will stay on paper
The concept of EHF is very good, but I think it’s a long term project. The potential is huge but the project will need time to develop more the concept and make some partnerships I think.
You think it's a long term project?well.. that should have been clear from the start, looking at the roadmap
)many people are expecting a project to deliver the goods in a year or so. this one will take a long time cause it's such a complex endevour.
Most crypto projects are still in beta or not even that. Even whitepapers can reach a billion dollar market cap. eHealth is honest about the long roadmap. That could pay off in the end.
Most importantly i think they have been able to define what real problems they are going to solve and how.
Sometimes good idea can stay on paper so Hopefully ehealth wont be like them.
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