Cureus,
Journal Year:
2025,
Volume and Issue:
unknown
Published: Jan. 27, 2025
To
obtain
detailed
data
on
the
acceptance
of
an
artificial
intelligence
chatbot
(ChatGPT;
OpenAI,
San
Francisco,
CA,
USA)
in
ophthalmology
among
physicians,
a
survey
explored
physician
responses
regarding
using
ChatGPT
ophthalmology.
The
included
questions
about
applications
ophthalmology,
future
concerns
such
as
job
replacement
or
automation,
research,
medical
education,
patient
ethical
concerns,
and
implementation
practice.
One
hundred
ninety-nine
ophthalmic
surgeons
participated
this
study.
Approximately
two-thirds
participants
had
15
years
more
experience
sixteen
reported
that
they
used
ChatGPT.
We
found
no
difference
age,
gender,
level
between
those
who
did
not
use
users
tend
to
consider
(AI)
useful
(P=0.001).
Both
non-users
think
AI
is
for
identifying
early
signs
eye
disease,
providing
decision
support
treatment
planning,
monitoring
progress,
answering
questions,
scheduling
appointments.
believe
there
are
some
issues
related
health
care,
liability
issues,
privacy
accuracy
diagnosis,
trust
chatbot,
information
bias.
other
forms
increasingly
becoming
accepted
ophthalmologists.
seen
helpful
tool
improving
support,
services,
but
also
displacement,
which
warrant
human
oversight.
Diagnostics,
Journal Year:
2024,
Volume and Issue:
14(7), P. 694 - 694
Published: March 26, 2024
Artificial
intelligence
(AI)
has
seen
significant
progress
in
medical
diagnostics,
particularly
image
and
video
analysis.
This
review
focuses
on
the
application
of
AI
analyzing
vivo
confocal
microscopy
(IVCM)
images
for
corneal
diseases.
The
cornea,
as
an
exposed
delicate
part
body,
necessitates
precise
diagnoses
various
conditions.
Convolutional
neural
networks
(CNNs),
a
key
component
deep
learning,
are
powerful
tool
data
highlights
applications
diagnosing
keratitis,
dry
eye
disease,
diabetic
neuropathy.
It
discusses
potential
detecting
infectious
agents,
nerve
morphology,
identifying
subtle
changes
fiber
characteristics
However,
challenges
still
remain,
including
limited
datasets,
overfitting,
low-quality
images,
unrepresentative
training
datasets.
explores
augmentation
techniques
importance
feature
engineering
to
address
these
challenges.
Despite
made,
present,
such
“black-box”
nature
models
need
explainable
(XAI).
Expanding
fostering
collaborative
efforts,
developing
user-friendly
tools
crucial
enhancing
acceptance
integration
into
clinical
practice.
Ophthalmology Science,
Journal Year:
2024,
Volume and Issue:
4(5), P. 100518 - 100518
Published: March 22, 2024
This
study
aimed
to
propose
a
fully
automatic
eyelid
measurement
system
and
compare
the
contours
of
both
upper
lower
eyelids
normal
individuals
according
age
gender.
IP International Journal of Ocular Oncology and Oculoplasty,
Journal Year:
2025,
Volume and Issue:
10(4), P. 196 - 207
Published: Jan. 14, 2025
In
the
domains
of
ocular
oncology
and
oculoplasty,
machine
learning
(ML)
has
become
a
game-changing
technology,
providing
previously
unheard-of
levels
precision
in
diagnosis,
treatment
planning,
outcome
prediction.
Using
imaging
modalities,
genomic
data,
clinical
characteristics,
this
chapter
investigates
integration
algorithms
detection
tumours,
including
retinoblastoma
uveal
melanoma.
Through
predictive
modelling
real-time
decision-making,
it
also
emphasises
how
ML
might
improve
surgical
outcomes
orbital
reconstruction
eyelid
correction.
Automated
examination
fundus
photographs,
histological
slides,
3D
been
made
possible
by
methods
like
deep
natural
language
processing,
which
have
improved
individualised
therapeutic
approaches
decreased
diagnostic
errors.
Additionally,
use
augmented
reality
robotics
surgery
is
significant
development
oculoplasty.
Notwithstanding
its
potential,
issues
data
heterogeneity,
algorithm
interpretability,
ethical
considerations
are
roadblocks
that
need
to
be
addressed.
This
explores
cutting-edge
developments,
real-world
uses,
potential
future
paths,
offering
researchers
doctors
thorough
resource.
Dipali
Vikas
Mane,
Associate
Professor,
Shriram
Shikshan
Sanstha’s
College
Pharmacy,
Paniv-413113
Cureus,
Journal Year:
2025,
Volume and Issue:
unknown
Published: Jan. 27, 2025
To
obtain
detailed
data
on
the
acceptance
of
an
artificial
intelligence
chatbot
(ChatGPT;
OpenAI,
San
Francisco,
CA,
USA)
in
ophthalmology
among
physicians,
a
survey
explored
physician
responses
regarding
using
ChatGPT
ophthalmology.
The
included
questions
about
applications
ophthalmology,
future
concerns
such
as
job
replacement
or
automation,
research,
medical
education,
patient
ethical
concerns,
and
implementation
practice.
One
hundred
ninety-nine
ophthalmic
surgeons
participated
this
study.
Approximately
two-thirds
participants
had
15
years
more
experience
sixteen
reported
that
they
used
ChatGPT.
We
found
no
difference
age,
gender,
level
between
those
who
did
not
use
users
tend
to
consider
(AI)
useful
(P=0.001).
Both
non-users
think
AI
is
for
identifying
early
signs
eye
disease,
providing
decision
support
treatment
planning,
monitoring
progress,
answering
questions,
scheduling
appointments.
believe
there
are
some
issues
related
health
care,
liability
issues,
privacy
accuracy
diagnosis,
trust
chatbot,
information
bias.
other
forms
increasingly
becoming
accepted
ophthalmologists.
seen
helpful
tool
improving
support,
services,
but
also
displacement,
which
warrant
human
oversight.
