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Giving Hope and Improving Lives with Cognitive Technology | Deborah DiSanzo | TEDxBeaconStreet


could you imagine with me for a moment

could you imagine with me for a moment that you’re sitting with somewhere on a

that you’re sitting with somewhere on a

that you’re sitting with somewhere on a Friday afternoon at two-30 your phone

Friday afternoon at two-30 your phone

Friday afternoon at two-30 your phone rings you don’t recognize the number

rings you don’t recognize the number

rings you don’t recognize the number but you answer it and you hear a rather

but you answer it and you hear a rather

but you answer it and you hear a rather cold voice from the phone and the voice

cold voice from the phone and the voice

cold voice from the phone and the voice says hello I’m dr. Smith that breast

says hello I’m dr. Smith that breast

says hello I’m dr. Smith that breast biopsy you had we found a tumor it’s

biopsy you had we found a tumor it’s

biopsy you had we found a tumor it’s cancer your mind goes blank your heart

cancer your mind goes blank your heart

cancer your mind goes blank your heart starts to race your fingers go numb you

starts to race your fingers go numb you

starts to race your fingers go numb you think about your daughter

think about your daughter

think about your daughter you think about your husband you think

you think about your husband you think

you think about your husband you think about your life and that phone call you

about your life and that phone call you

about your life and that phone call you manage to make an appointment with that

manage to make an appointment with that

manage to make an appointment with that breast surgeon plus two more three

breast surgeon plus two more three

breast surgeon plus two more three oncologists and three radio radiation

oncologists and three radio radiation

oncologists and three radio radiation oncologists at the end of two weeks this

oncologists at the end of two weeks this

oncologists at the end of two weeks this is what you know your invasive lobular

is what you know your invasive lobular

is what you know your invasive lobular breast cancer could be four millimeters

breast cancer could be four millimeters

breast cancer could be four millimeters in size it could be eight millimeters

in size it could be eight millimeters

in size it could be eight millimeters meters in size it could be 2.5

meters in size it could be 2.5

meters in size it could be 2.5 centimeters in size when breast surgeon

centimeters in size when breast surgeon

centimeters in size when breast surgeon says in the secta me 1 breast surgeon

says in the secta me 1 breast surgeon

says in the secta me 1 breast surgeon says a lumpectomy one oncologist says

says a lumpectomy one oncologist says

says a lumpectomy one oncologist says you will have chemotherapy and other

you will have chemotherapy and other

you will have chemotherapy and other says you won’t one rat honk says you’ll

says you won’t one rat honk says you’ll

says you won’t one rat honk says you’ll have 29 days of radiation but the second

have 29 days of radiation but the second

have 29 days of radiation but the second one says eight weeks and the third one

one says eight weeks and the third one

one says eight weeks and the third one says you don’t need radiation at all

says you don’t need radiation at all

says you don’t need radiation at all I’ve got a clinical trial and at the end

I’ve got a clinical trial and at the end

I’ve got a clinical trial and at the end of this there are three hormonal drugs

of this there are three hormonal drugs

of this there are three hormonal drugs you can go on really really is this the

you can go on really really is this the

you can go on really really is this the best we have isn’t one of these

best we have isn’t one of these

best we have isn’t one of these treatments better than the other which

treatments better than the other which

treatments better than the other which one is going to work best for me what

one is going to work best for me what

one is going to work best for me what about patients like me

about patients like me

about patients like me worked for them unfortunately this is

worked for them unfortunately this is

worked for them unfortunately this is the reality of cancer diagnosis and

the reality of cancer diagnosis and

the reality of cancer diagnosis and treatment today you see some cancers are

treatment today you see some cancers are

treatment today you see some cancers are difficult to see in our medical images

difficult to see in our medical images

difficult to see in our medical images some pathologies are hard to read the

some pathologies are hard to read the

some pathologies are hard to read the elect Everage electronic health record

elect Everage electronic health record

elect Everage electronic health record is the size of a Harry Potter book

is the size of a Harry Potter book

is the size of a Harry Potter book eight thousand new research papers are

eight thousand new research papers are

eight thousand new research papers are being being written every day and some

being being written every day and some

being being written every day and some say that if our oncologists need to read

say that if our oncologists need to read

say that if our oncologists need to read everything that they needed to read

everything that they needed to read

everything that they needed to read they’d be reading 20 hours a day but

they’d be reading 20 hours a day but

they’d be reading 20 hours a day but Watson is a cognitive computer and

Watson is a cognitive computer and

Watson is a cognitive computer and Watson can help you see Watson reads and

Watson can help you see Watson reads and

Watson can help you see Watson reads and he reads fast so he can read my

he reads fast so he can read my

he reads fast so he can read my electronic health record both the

electronic health record both the

electronic health record both the structured in the unstructured text in

structured in the unstructured text in

structured in the unstructured text in the structured text he’ll find my name

the structured text he’ll find my name

the structured text he’ll find my name my Democratic my demographics my

my Democratic my demographics my

my Democratic my demographics my clinical information but in the

clinical information but in the

clinical information but in the unstructured text he may find

unstructured text he may find

unstructured text he may find information in a doctor’s note that

information in a doctor’s note that

information in a doctor’s note that could help in my diagnosis it could be

could help in my diagnosis it could be

could help in my diagnosis it could be that my parents were smokers or that I

that my parents were smokers or that I

that my parents were smokers or that I took birth control pills in my 20s and

took birth control pills in my 20s and

took birth control pills in my 20s and Watson reads images we’ve trained Watson

Watson reads images we’ve trained Watson

Watson reads images we’ve trained Watson to read the tens of thousands of images

to read the tens of thousands of images

to read the tens of thousands of images we’re teaching Watson to read what

we’re teaching Watson to read what

we’re teaching Watson to read what humans cannot see cognitive compute

humans cannot see cognitive compute

humans cannot see cognitive compute computing Watson reads he learns from

computing Watson reads he learns from

computing Watson reads he learns from what he reads he never forgets what he

what he reads he never forgets what he

what he reads he never forgets what he reads he doesn’t get tired and after he

reads he doesn’t get tired and after he

reads he doesn’t get tired and after he learns from what he reads he makes a

learns from what he reads he makes a

learns from what he reads he makes a probable recommendation of what could

probable recommendation of what could

probable recommendation of what could happen in the case of cancer he helps

happen in the case of cancer he helps

happen in the case of cancer he helps your physician understand what your

your physician understand what your

your physician understand what your diagnosis is and what the treatment can

diagnosis is and what the treatment can

diagnosis is and what the treatment can be Watson has read millions of research

be Watson has read millions of research

be Watson has read millions of research papers he’s read three hundred medical

papers he’s read three hundred medical

papers he’s read three hundred medical journals 200 medical textbooks

journals 200 medical textbooks

journals 200 medical textbooks we’ve trained him on tens of millions of

we’ve trained him on tens of millions of

we’ve trained him on tens of millions of de-identified patient records and the

de-identified patient records and the

de-identified patient records and the best oncologist in the world have

best oncologist in the world have

best oncologist in the world have trained Watson we’re making it so

trained Watson we’re making it so

trained Watson we’re making it so whether you’re in Boston or whether

whether you’re in Boston or whether

whether you’re in Boston or whether you’re in New York City or whether

you’re in New York City or whether

you’re in New York City or whether you’re in rural Montana or China you can

you’re in rural Montana or China you can

you’re in rural Montana or China you can get

get

get the same advice on your cancer diagnosis

the same advice on your cancer diagnosis

the same advice on your cancer diagnosis and your treatment and we can go further

and your treatment and we can go further

and your treatment and we can go further with Watson for genomics if your cancer

with Watson for genomics if your cancer

with Watson for genomics if your cancer is advanced or a corner case we can read

is advanced or a corner case we can read

is advanced or a corner case we can read in the genetic profile of your cancer

in the genetic profile of your cancer

in the genetic profile of your cancer and Watson can match match it with a

and Watson can match match it with a

and Watson can match match it with a drug at University of North Carolina

drug at University of North Carolina

drug at University of North Carolina we trained Watson for genomics

we trained Watson for genomics

we trained Watson for genomics retrospectively on 1,000 patients and we

retrospectively on 1,000 patients and we

retrospectively on 1,000 patients and we found in those 1,000 patients Watson

found in those 1,000 patients Watson

found in those 1,000 patients Watson agreed with the oncologist 99 percent of

agreed with the oncologist 99 percent of

agreed with the oncologist 99 percent of the time you’re very happy Watson had

the time you’re very happy Watson had

the time you’re very happy Watson had learned but in 1 percent of the time

learned but in 1 percent of the time

learned but in 1 percent of the time which turned out to be 300 patients

which turned out to be 300 patients

which turned out to be 300 patients Watson recommended a different

Watson recommended a different

Watson recommended a different medication was Watson right

medication was Watson right

medication was Watson right turns out Watson was right Watson found

turns out Watson was right Watson found

turns out Watson was right Watson found medications that came out in 2013 2014

medications that came out in 2013 2014

medications that came out in 2013 2014 in 2015 that could help these patients

in 2015 that could help these patients

in 2015 that could help these patients but are overworked oncologists simply

but are overworked oncologists simply

but are overworked oncologists simply hadn’t seen them in an October the

hadn’t seen them in an October the

hadn’t seen them in an October the Japanese Times wrote this there was a

Japanese Times wrote this there was a

Japanese Times wrote this there was a woman who entered University of Tokyo

woman who entered University of Tokyo

woman who entered University of Tokyo she was a 60 year old woman last January

she was a 60 year old woman last January

she was a 60 year old woman last January and she had an advanced form of leukemia

and she had an advanced form of leukemia

and she had an advanced form of leukemia she went on chemotherapy and the

she went on chemotherapy and the

she went on chemotherapy and the chemotherapy worked to attack her cancer

chemotherapy worked to attack her cancer

chemotherapy worked to attack her cancer cells but she wasn’t getting better in

cells but she wasn’t getting better in

cells but she wasn’t getting better in August the researchers decided to read

August the researchers decided to read

August the researchers decided to read her genetic profile into Watson she had

her genetic profile into Watson she had

her genetic profile into Watson she had 1,000 gene mutations what would have

1,000 gene mutations what would have

1,000 gene mutations what would have taken scientists 2 weeks to go through

taken scientists 2 weeks to go through

taken scientists 2 weeks to go through Watson read in 10 minutes and with

Watson read in 10 minutes and with

Watson read in 10 minutes and with cancer time is important Watson found an

cancer time is important Watson found an

cancer time is important Watson found an underlying secondary leukemia that could

underlying secondary leukemia that could

underlying secondary leukemia that could be treated with another drug the

be treated with another drug the

be treated with another drug the Japanese Times reported that treatment

Japanese Times reported that treatment

Japanese Times reported that treatment started in September and she went home

started in September and she went home

started in September and she went home what does all this mean we’re only at

what does all this mean we’re only at

what does all this mean we’re only at the very beginning we have not read in

the very beginning we have not read in

the very beginning we have not read in every cancer we have not read in every

every cancer we have not read in every

every cancer we have not read in every drug but certainly within the next

drug but certainly within the next

drug but certainly within the next decade

decade

decade the next time my cancer is diagnosed

the next time my cancer is diagnosed

the next time my cancer is diagnosed Watson will help my oncologist prescribe

Watson will help my oncologist prescribe

Watson will help my oncologist prescribe a treatment exactly for me not for

a treatment exactly for me not for

a treatment exactly for me not for 10,000 mythical woman’s somehow like me

10,000 mythical woman’s somehow like me

10,000 mythical woman’s somehow like me but a treatment just for me artificial

but a treatment just for me artificial

but a treatment just for me artificial intelligence sure but we call Watson

intelligence sure but we call Watson

intelligence sure but we call Watson augmented intelligence we call Watson

augmented intelligence we call Watson

augmented intelligence we call Watson the learner colleague because what we’re

the learner colleague because what we’re

the learner colleague because what we’re doing is helping these hard-working

doing is helping these hard-working

doing is helping these hard-working physicians diagnose and treat my entire

physicians diagnose and treat my entire

physicians diagnose and treat my entire working career all I’ve wanted to do is

working career all I’ve wanted to do is

working career all I’ve wanted to do is make a difference in the intersection of

make a difference in the intersection of

make a difference in the intersection of healthcare and technology and now me in

healthcare and technology and now me in

healthcare and technology and now me in the extraordinarily talented team at IBM

the extraordinarily talented team at IBM

the extraordinarily talented team at IBM Watson health gets to do just that we

Watson health gets to do just that we

Watson health gets to do just that we save lives and give hope to the world’s

save lives and give hope to the world’s

save lives and give hope to the world’s most pressing health care challenges

most pressing health care challenges

most pressing health care challenges through the power of data in cognitive

through the power of data in cognitive

through the power of data in cognitive computing thank you

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