The potential of Artificial Intelligence in Healthcare Industry - PowerPoint PPT Presentation

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The potential of Artificial Intelligence in Healthcare Industry

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The future of AI in healthcare are strong and AI has the capacity to transform healthcare. However, AI also faces considerable obstacles and potential threats, such as worries about privacy and security, reliance on technology, etc., To guarantee that AI is utilised ethically and responsibly, it is crucial to address Artificial Intelligence in healthcare with care and thoroughly assess its possible benefits and pitfalls. – PowerPoint PPT presentation

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Title: The potential of Artificial Intelligence in Healthcare Industry


1
The potential of Artificial Intelligence in
Healthcare Industry
March 30, 2023 Dash Technologies Inc Artificial
Intelligence, Healthcare, Machine Learning,
Technology
About AI Aítificial intelligence is a topic that,
in its most basic foím, integíates computeí
science and substantial datasets to facilitate
píoblem-solving. Moíeoveí, it includes the
bíanches of aítificial intelligence known as deep
leaíning and machine leaíning, which aíe
commonly addíessed togetheí.
2
How healthcare industry is changing by adopting
technology?
lhe following aíe some of the most íiveting
impacts of Aítificial Intelligence in the
healthcaíe sectoí
  • Incíeased Inteíaction
  • Healthcaíe businesses now have betteí
    communication thanks to emeíging technology.
    Moíe numbeí of medical píofessionals aíe using
    technology to communicate and advance the
    industíy, including videoconfeíencing, AR/VR,
    etc., Moíeoveí, teleconfeíencing has simplified
    communication acíoss geogíaphical boundaíies.
  • Digital Health Recoíds
  • Digital medical íecoíds assist in saving details
    of a peísons health histoíy digitally, putting
    an end to the days of hefty files and tatteíed
    papeís. Lab íesults, diagnoses, suígical
    píoceduíes, píescíiptions, and even infoímation
    about hospital stays may be included in the
    digital summaíy. Betteí health insights píovided
    by electíonic medical data can lead to moíe
    píecise diagnoses and higheí-quality patient
    caíe.
  • Big Data
  • Medical accountants can quickly gatheí enoímous
    data thanks to health technology. Healthcaíe
    píactitioneís can betteí compíehend and leaín
    about modeín methods and tíends with the aid of
    data collecting.
  • Enhancing Patient Caíe lhe healthcaíe industíy
    now has cutting-edge instíuments at its disposal
    to

3
  • enhance patient caíe. Physicians may quickly
    access a patients full medical
  • histoíy using EHRs and make educated decisions.
  • AI applications in healthcare
  • lheíe aíe numeíous AI applications in healthcaíe
  • Medical Imaging
  • Using ML in healthcaíe and otheí algoíithms may
    examine medical pictuíes such as X-íays, MRIs,
    and Cl scans to assist íadiologists in moíe
    accuíately identifying anomalies. Ïuítheímoíe,
    it can aid in the timely identification of
    illnesses like canceí.
  • Díug Discoveíy
  • By examining sizable databases of bioactive
    molecules and píojecting theií effectiveness in
    cuíing paíticulaí ailments, ML in healthcaíe can
    assist in the identification of possible
    medication candidates.

Medicine AI can assist in the development of ind
ividualized tíeatment
  • Customized

íecommendations foí individuals accoíding to
theií health histoíies, genetic makeup, and
lifestyle choices.
  • Electíonic Health

Recoíds
AI can examine EHRs to find patteíns and tíends
that can assist physicians in making moíe
educated decisions íegaíding a patients caíe.
  • VNA (Viítual

Nuísing Assistant)
  • lhey can suppoít patients in managing chíonic
    diseases by íeminding them to take theií
    medications, exeícise, oí keep theií scheduled
    appointments.
  • Píedictive Analysis
  • With the help of AI, it is possible to estimate
    the íisk that a patient will develop a ceítain
    disease, and to take píeventative and eaíly
    action measuíes.

4
  • Robotics
  • AI-poweíed íobots can suppoít suígeons duíing
    opeíations by supplying íeal- time data and
    photos, enabling moíe accuíate and effective
    suígeíy.
  • Latest trends in the Healthcare Industry
  • Aítificial

Intelligence
AI is íeplacing tíaditional, labouí and time
intensive healthcaíe píocesses with quick,
íemote-access, and íealistic solutions. lo
maximize the potential of AI, health-tech
businesses píovide digital platfoíms, APIs, and
otheí digital goods.
  • Inteínet of

Health lhings
  • lhe cíeation of devices that íequiíe little to no
    human contact to deliveí healthcaíe seívices is
    made possible by IoMl. Many AI applications,
    including automatic steíilization, smaít
    diagnostics, and íemote patient caíe, etc., aíe
    made possible by electíonic medical equipment,
    and infíastíuctuíe.
  • lelemedicine
  • Seveíal goveínments, healthcaíe systems, doctoís,
    and patients adopted telemedicine moíe quickly
    as a íesult of the COVID-19 epidemic.
  • Goveínments íeleased telemedicine guidelines to
    íelieve píessuíe on healthcaíe institutions as a
    íesponse to the pandemic.
  • 3D-Píinting
  • In the healthcaíe sectoí, 3D píinting is becoming
    moíe populaí foí a vaíiety of uses, including
    píoducing bionics, casts foí fíactuíe
    íehabilitation, and lightweight píosthetics.
    Using the patients own medical imaging, 3D
    píinting techniques aíe enabling the cíeation of
    patient-specific veísions of oígans and medical
    tools.

5
Challenges faced by healthcare in AI Adoption
  • Lack of standaídization lhe lack of consistency
    is one of the majoí obstacles to the use of AI in
    health sectoí. lheíe aíe cuííently no accepted
    guidelines foí the application of AI in
    healthcaíe settings. Both patients and healthcaíe
    píovideís may expeíience challenges as a íesult
    of this lack of unifoímity.
  • Limited Data
  • In oídeí to enhance patient caíe and outcomes,
    healthcaíe oíganisations have íecently
    implemented AI. Limited data, howeveí, is a
    seíious obstacle in this effoít. AI model
    tíaining is challenging because health data is
    fíequently segíegated and difficult to access.
  • Adaptation to existing systems Integíating AI
    with legacy systems is one of the difficulties in
    applying it to
  • healthcaíe. Most legacy systems aíe built on
    antiquated technology that aíe unsuitable with
    moíe modeín ones. Data inteíchange between these
    systems íequiíed foí AI applications, may be
    challenging as a íesult.
  • High Costs
  • Anotheí issue with implementing AI is its high
    cost acíoss the boaíd. Although AI has a wide
    íange of potential applications in the healthcaíe
    industíy, the high expenses associated with its
    development and deployment continue to
  • be a majoí obstacle to its wide acceptance.

6
Pros and Cons of AI in the health sector
  • Díawbacks of Aítificial Intelligence in
    healthcaíe
  • Following aíe the díawbacks of AI in healthcaíe
  • Enhanced diagnostic accuíacy A higheí degíee of
    diagnostic accuíacy is possible thanks to AI
    softwaíe development and AI development
    seívices, which can evaluate vast volumes of
    medical data and suppoít doctoís in making
    píecise diagnoses, paíticulaíly foí complicated
    medical illnesses that can be challenging to
    identify with conventional techniques.
  • Impíoved tíeatment planning Peísonalized
    tíeatment íegimens can be made with the use of AI
    softwaíe development, AI development seívices
    and píogíams, which can examine patient data.
  • Reduced costs
  • Cost-effectiveness impíovements and a decline in
    the demand foí píicey diagnostic testing aíe two
    ways AI can assist save healthcaíe expenses.
  • Betteí patient outcomes
  • AI softwaíe development seívices and stíategies
    can assist in identifying individuals who aíe at
    high íisk of contíacting majoí illnesses,
    allowing clinicians to take eaíly action and
    peíhaps stop the beginning of sickness.
  • Benefits of AI in healthcare
  • Following aíe the benefits of AI in healthcaíe
  • Risks to píivacy and secuíity AI systems have
    the potential to gatheí and keep a lot of
    infoímation on an individuals health, which is
    susceptible to data theft and misuse.

7
  • Bias and

discíimination
If the dataset is not sufficiently vaíied, AI
systems may íeinfoíce cuííent biases and
discíimination.
  • Dependency on

technology
  • As AI in healthcaíe gíows incíeasingly impoítant,
    theíe is a chance that healthcaíe woíkeís will
    íely too heavily on it and lose sight of the
    impoítance of cíitical thinking.
  • Absence of human touch While AI systems can
    offeí a plethoía of data and analytics, they
    cannot take the place of a patients potential
    need foí a human touch and compassion.
  • Conclusion Future of AI in healthcare
  • lo conclude, the futuíe of AI in healthcaíe aíe
    stíong and AI has the capacity to tíansfoím
    healthcaíe. Howeveí, AI also faces consideíable
    obstacles and potential thíeats, such as woííies
    about píivacy and secuíity, íeliance on
    technology, etc., lo guaíantee that AI is
    utilised ethically and íesponsibly, it is cíucial
    to addíess Aítificial Intelligence in healthcaíe
    with caíe and thoíoughly assess its possible
    benefits and pitfalls.
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