With
the
advent
of
Healthcare
4.0,
there
is
increased
interest
from
researchers
world
over
in
application
modern,
cutting-edge
Artificial
Intelligence
(AI)
and
Quantum
(QAI)
algorithms
solving
healthcare
challenges.The
era
Computing
(QC)
promises
to
bring
significant
advancements
several
areas
such
that
it
may
be
sensible
give
this
hybrid
Quantum/Classical
paradigm
its
own
name
-Healthcare4Q.The
potential
QC
will
extend
reach
Healthcare4Q
with
help
diverse
technologies
as
quantum-enabled
wearables,
quantum-secure
transfer
storage
data,
quantum
computing
at
edge,
fog,
cloud.All
these
promise
catapult
become
most
capable
framework
advancement
medical
innovations
improvement
patient
care.An
integral
part
a
person's
health
lies
cardiovascular
health,
thus
prioritizing
optimizing
remains
vital
broader
goals
public
sustainability.In
study,
under
Healthcare4Q,
we
propose
called
AIdriven
Heart
Health
Framework
(QAIHHF)
can
provide
advanced
predictive
intelligence
providers
by
utilizing
historical
real-time
data
processing
capabilities
proposed
Healthcare4Q.We
show
when
applied
various
diagnostics
indicators
ECG
AI
provides
accuracy
level
equal
or
higher
compared
classical
methods
proving
itself
critical
component
herald
Healthcare4Q.
Algorithms,
Journal Year:
2025,
Volume and Issue:
18(3), P. 156 - 156
Published: March 9, 2025
Medical
decision-making
is
increasingly
integrating
quantum
computing
(QC)
and
machine
learning
(ML)
to
analyze
complex
datasets,
improve
diagnostics,
enable
personalized
treatments.
While
QC
holds
the
potential
accelerate
optimization,
drug
discovery,
genomic
analysis
as
hardware
capabilities
advance,
current
implementations
remain
limited
compared
classical
in
many
practical
applications.
Meanwhile,
ML
has
already
demonstrated
significant
success
medical
imaging,
predictive
modeling,
decision
support.
Their
convergence,
particularly
through
(QML),
presents
opportunities
for
future
advancements
processing
high-dimensional
healthcare
data
improving
clinical
outcomes.
This
review
examines
foundational
concepts,
key
applications,
challenges
of
these
technologies
healthcare,
explores
their
synergy
solving
problems,
outlines
directions
quantum-enhanced
decision-making.
Medical Sciences,
Journal Year:
2024,
Volume and Issue:
12(4), P. 67 - 67
Published: Nov. 17, 2024
Quantum
computing
(QC)
represents
a
paradigm
shift
in
computational
power,
offering
unique
capabilities
for
addressing
complex
problems
that
are
infeasible
classical
computers.
This
review
paper
provides
detailed
account
of
the
current
state
QC,
with
particular
focus
on
its
applications
within
medicine.
It
explores
fundamental
concepts
such
as
qubits,
superposition,
and
entanglement,
well
evolution
QC
from
theoretical
foundations
to
practical
advancements.
The
covers
significant
milestones
where
has
intersected
medical
research,
including
breakthroughs
drug
discovery,
molecular
modeling,
genomics,
diagnostics.
Additionally,
key
quantum
techniques
algorithms,
machine
learning
(QML),
quantum-enhanced
imaging
explained,
highlighting
their
relevance
healthcare.
also
addresses
challenges
field,
hardware
limitations,
scalability,
integration
clinical
environments.
Looking
forward,
discusses
potential
quantum–classical
hybrid
systems
emerging
innovations
hardware,
suggesting
how
these
advancements
may
accelerate
adoption
research
practice.
By
synthesizing
reliable
knowledge
presenting
it
through
comprehensive
lens,
this
serves
valuable
reference
researchers
interested
transformative
IEEE Access,
Journal Year:
2024,
Volume and Issue:
12, P. 62215 - 62233
Published: Jan. 1, 2024
Chronic
diseases,
a
global
public
health
challenge,
necessitate
the
deployment
of
cutting-edge
predictive
models
for
early
diagnosis
and
personalized
interventions.
This
study
presents
an
advanced
methodology
prediction
chronic
including
heart
attack,
diabetes,
breast
cancer,
kidney
disease,
leveraging
synergistic
combination
techniques.
Recognizing
challenge
posed
by
extensive
medical
datasets
with
numerous
features,
we
introduce
novel
approach
that
begins
Feature
Engineering
using
Recursive
Elimination
(RFE)
in
conjunction
Support
Vector
Machine
(SVM).
The
presented
identifies
removes
irrelevant
features
to
simplify
data
complexity.
refined
dataset
is
then
input
into
robust
eXtreme
Gradient
Boosting
(XGBoost)
classifier,
known
its
efficiency
adeptness
predicting
complex
relationships
within
data.
chosen
ensemble
learning
algorithm
demonstrates
significant
prowess
inducing
intricate
patterns
crucial
disease
prediction.
To
enhance
model
performance,
essential
phase
optimization
introduced
through
hyperparameter
tuning
Bayesian
optimization.
strategically
navigates
space,
maximizing
search
process
fine-tuning
optimal
accuracy.
proposed
showcases
substantial
improvement
demonstrating
effectiveness
approach.
Journal of X-Ray Science and Technology,
Journal Year:
2024,
Volume and Issue:
32(4), P. 857 - 911
Published: April 30, 2024
The
emergence
of
deep
learning
(DL)
techniques
has
revolutionized
tumor
detection
and
classification
in
medical
imaging,
with
multimodal
imaging
(MMI)
gaining
recognition
for
its
precision
diagnosis,
treatment,
progression
tracking.
Frontiers in Public Health,
Journal Year:
2025,
Volume and Issue:
12
Published: Jan. 7, 2025
Hyper-personalized
medicine
represents
the
cutting
edge
of
healthcare,
which
aims
to
tailor
treatment
and
prevention
strategies
uniquely
each
individual.
Unlike
traditional
approaches,
often
adopt
a
one-size-fits-all
or
even
broadly
personalized
approach
based
on
broad
genetic
categories,
hyper-personalized
considers
an
individual's
comprehensive
health
data
by
integrating
unique
biological,
genetic,
lifestyle,
environmental
influences.
This
method
goes
beyond
simple
profiling
recognizing
that
outcomes
are
influenced
complex
interactions
among
our
environment,
daily
routines,
physiological
processes
responses.Central
is
integration
lifestyle
factors.
Lifestyle
habits,
such
as
diet
(Dalwood
et
al.,
2020;
Genel
Marx
Hepsomali
&
Groeger,
2021;
Dinu
2022;
Yang
Sadler
2024),
exercise
(Chow
Qiu
Ross
D'Onofrio
2023;
Isath
Mahindru
Ashcroft
2024;
Ponzano
sleep
patterns
(Hepsomali
Baranwal
Eshera
Lim
Sletten
Uccella,
Weinberger
2023),
directly
impact
health.
Hence,
understanding
these
factors
helps
interventions
align
with
day-to-day
realities
Environmental
factors,
air
quality
(Cheek
Markandeya
Shukla
Tang
Abdul-Rahman
Bedi
Bhattacharya,
climate
(Coates
Ebi
Helldén
Reismann
Rocque
Zhang
Münzel
Palmeiro-Silva
exposure
pollutants
(Qadri
Faiq,
2019;
Petroni
Lin
Sun
Xu
Yu
Levin
Shetty
Deziel
Villanueva
Sharma
also
play
significant
roles
in
determining
outcomes.
By
continuously
monitoring
analyzing
elements,
healthcare
providers
can
create
dynamic
plans
adapt
real-time
changes.
would
allow
for
proactive
measures
optimized
care.To
enable
model
care,
advanced
technologies
like
quantum
computing,
artificial
general
intelligence
(AGI),
internet
things
(IoT),
6G
connectivity
crucial
roles.
Quantum
computing
offers
ability
process
vast
intricate
datasets,
those
required
between
markers,
exposures,
choices,
far
greater
speed
accuracy
than
classical
(Munshi
Kumar
Stefano,
Ullah
Garcia-Zapirain,
2024).
AGI,
its
adaptive
learning
capabilities,
analyze
make
sense
this
provide
precise,
evolving
recommendations
change
patient's
environment
does
(Liu
Mitchell,
Tu
IoT
devices,
including
wearables
sensors,
gather
continuous
from
individuals,
tracking
physical
activity,
biometrics,
conditions
humidity
(Puri
Islam
Mathkor
Rocha
Šajnović
Salam,
With
advent
connectivity,
seamlessly
transferred
processed
real
time,
enabling
instant
feedback
intervention
(Nayak
Patgiri,
Nguyen
Ahad
Kumar,
Kaur,
Mahmood
Mihovska
2024).Together,
form
backbone
model,
will
push
medical
practices
highly
responsive,
individual-centered
As
advancements
continue
evolve,
has
potential
fundamentally
reshape
offering
truly
support
long-term
well-being.
