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Could Artificial Intelligence
Help Identify Your Risk To Serious Illness And Disease
At first glance, it would seem that the human body is too
complicated for artificial intelligence (AI) to comprehend. But Artificial
Intelligence is quickly becoming one of the most critical technologies in
healthcare with its ability to diagnose and predict disease.
Some interesting examples include using machine learning
algorithms to predict your risk of heart attack or stroke, spotting undiagnosed
diabetes in emergency room patients, and synthesizing a virtual endocannabinoid
system using artificial
neural networks . It’s not surprising that the number of AI
providers has grown four-fold over the past five years; this is expected to
continue as insurers and payers move away from fee-for-service payments for
healthcare services towards more value-based models.
AI to predic t stroke and heart attack risk by
scanning retinas
One of the biggest problems in medicine is det
ermining who is
at an increased risk for a stroke or heart attack. The reasons are many, but it
might have to do with people not wanting to get screened or not knowing how
important it is. In addition, health insurance companies often have
one-size-fits-all rules when it comes to caring and thus cannot consider which
needs extra care. Physician groups cannot be trusted either as there are often
have financial incentives to keep patients in their practice as long as possible.
The problem is that it has become increasingly easy for patients to
self-diagnose and self-treat based on information on the internet.
But it’s not just hospitals and healthcare providers who use AI to
make predictions about patients’ health. Insurance companies and telemedicine
providers such as labs and clinics use AI to determine their clients’ risk of
developing costly diseases such as diabetes, heart attack, stroke, or cancer.
A study out of IBM found
that AI can outperform patho
logists when predicting which type of cancer will
be diagnosed in a patient with a particular malignancy. AI can correctly
predict 97% of cases vs. 94% for pathologists for a person with lung cancer.
Another study identified five biomarkers that are associated with
patients who are at risk for diabetes and CVD .
The biomarkers were measured in EDTA plasma to determine each subject’s risk.
Using a multivariate hierarchical model, it was found that the subjects who
tested positive for all five biomarkers had an 85% chance of having diabetes
and a 50% chance of CVD. Of the subjects who tested positive for four out of
five biomarkers, 80% had diabetes, and 43% had CVD. And those who tested
positive for three out of five biomarkers had a 60% chance of having diabetes
and a 32% chance of CVD. And finally, those who tested positive for two out of
five biomarkers had a 36% chance of having diabetes and a 22% chance of CVD.
Biological traits vary from person to person, which means
that each individual can be at risk for severe illness and disease due to their
unique genetic
makeup . But there is no one-size-fits-all test for detecting
whether you are at risk for severe illness and disease. Your health insurance
provider would need to create a unique risk profile specific to your genetic
makeup; this would help determine what types of prevention, treatment, and
services they would offer you based on the amount they are willing to pay out
over your lifetime.
AI to predict stroke a nd heart attack risk by
scanning retinas
One of the biggest problems in medicine is determining who is at
an increased risk for a stroke or heart attack. The reasons are many, but it
might have to do with people not wanting to get screened or not knowing how
important it is. In addition, health insurance companies often have
one-size-fits-all rules when it comes to caring and thus cannot consider which
needs extra care. Physician groups cannot be trusted either as there are often
have financial incentives to keep patients in their practice as long as
possible. The problem is that it has become increasingly easy for patients to
self-diagnose and self-treat based on information on the internet.
Read
Full Article - https :// deeptechbytes . com / could - artificial - intelligence - help - identify - your - risk - to - serious - illness - and - disease /
Help Identify Your Risk To Serious Illness And Disease
At first glance, it would seem that the human body is too
complicated for artificial intelligence (AI) to comprehend. But Artificial
Intelligence is quickly becoming one of the most critical technologies in
healthcare with its ability to diagnose and predict disease.
Some interesting examples include using machine learning
algorithms to predict your risk of heart attack or stroke, spotting undiagnosed
diabetes in emergency room patients, and synthesizing a virtual endocannabinoid
system using artificial
neural networks . It’s not surprising that the number of AI
providers has grown four-fold over the past five years; this is expected to
continue as insurers and payers move away from fee-for-service payments for
healthcare services towards more value-based models.
AI to predic t stroke and heart attack risk by
scanning retinas
One of the biggest problems in medicine is det
ermining who is
at an increased risk for a stroke or heart attack. The reasons are many, but it
might have to do with people not wanting to get screened or not knowing how
important it is. In addition, health insurance companies often have
one-size-fits-all rules when it comes to caring and thus cannot consider which
needs extra care. Physician groups cannot be trusted either as there are often
have financial incentives to keep patients in their practice as long as possible.
The problem is that it has become increasingly easy for patients to
self-diagnose and self-treat based on information on the internet.
But it’s not just hospitals and healthcare providers who use AI to
make predictions about patients’ health. Insurance companies and telemedicine
providers such as labs and clinics use AI to determine their clients’ risk of
developing costly diseases such as diabetes, heart attack, stroke, or cancer.
A study out of IBM found
that AI can outperform patho
logists when predicting which type of cancer will
be diagnosed in a patient with a particular malignancy. AI can correctly
predict 97% of cases vs. 94% for pathologists for a person with lung cancer.
Another study identified five biomarkers that are associated with
patients who are at risk for diabetes and CVD .
The biomarkers were measured in EDTA plasma to determine each subject’s risk.
Using a multivariate hierarchical model, it was found that the subjects who
tested positive for all five biomarkers had an 85% chance of having diabetes
and a 50% chance of CVD. Of the subjects who tested positive for four out of
five biomarkers, 80% had diabetes, and 43% had CVD. And those who tested
positive for three out of five biomarkers had a 60% chance of having diabetes
and a 32% chance of CVD. And finally, those who tested positive for two out of
five biomarkers had a 36% chance of having diabetes and a 22% chance of CVD.
Biological traits vary from person to person, which means
that each individual can be at risk for severe illness and disease due to their
unique genetic
makeup . But there is no one-size-fits-all test for detecting
whether you are at risk for severe illness and disease. Your health insurance
provider would need to create a unique risk profile specific to your genetic
makeup; this would help determine what types of prevention, treatment, and
services they would offer you based on the amount they are willing to pay out
over your lifetime.
AI to predict stroke a nd heart attack risk by
scanning retinas
One of the biggest problems in medicine is determining who is at
an increased risk for a stroke or heart attack. The reasons are many, but it
might have to do with people not wanting to get screened or not knowing how
important it is. In addition, health insurance companies often have
one-size-fits-all rules when it comes to caring and thus cannot consider which
needs extra care. Physician groups cannot be trusted either as there are often
have financial incentives to keep patients in their practice as long as
possible. The problem is that it has become increasingly easy for patients to
self-diagnose and self-treat based on information on the internet.
Read
Full Article - https :// deeptechbytes . com / could - artificial - intelligence - help - identify - your - risk - to - serious - illness - and - disease /