Kendall Stout
Mentored by: Dr. Marni Fisher
What if Artificial Intelligence could Revolutionize Healthcare?
Benefits of AI in Healthcare:
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Does anyone know of some practical ways we use AI today?
Google Maps
Shopping
Recomendations
Netflix
recommendations
Social Media
Filters
Siri/Alexa
CHAT-GPT
But, what are the ethical concerns with it?
In 2018
only about 11% of American adults would be willing to share their health data with tech companies, versus 72% with physicians (Murdoch 3).
only about 31% say they are “confident” or “somewhat confident” in tech company data security
(Murdoch 3)
Bias: the choices made during the development and design process determine the finality of the product
The US Food and Drug Administration certifies the institutions who “develop and maintain” AI in the United States.
(Murdoch 2)
However, in the European Union, the European Commision proposed a legislation that creates a privacy and data protection plan similar to the European General Data Protection Regulation
(Murdoch 2)
1. Health Outcome Predictions
(Alowais et al. par. 20-25; Stafie et al. 11)
AI can scan electronic health records (EHRs) and make predictions.
( Alowais et al. pars. 20-25)
For example, artificial intelligence scanned EHRs in a study of 17,556 patients on antidepressants (Alowais et al. par. 20). The artificial intelligence accurately predicted the antidepressant responses for each patient.
( Alowais et al. pars. 20-25)
Artificial intelligence has also successfully predicted responses to chemotherapies with 80% accuracy in a study of 175 patients based on gene expressions.
( Alowais et al. pars. 20)
The accuracy can also assist in determining hospital readmissions based on social health, medical history, and comparable patient characteristics, in addition to facilitating helpful interventions that supplement patient health and reduce healthcare costs.
(Alowais et al. par. 25)
TL;DR:
AI can look at your health records and know how you’ll react to treatments, or even when you’ll need them.
Since 2017, Flo, a menstrual tracker, has been using neural networks (artificial intelligence) to predict periods and symptoms.
(Zaunova et al. e40427)
2. DIagnostic Optimization
(Bassani et al. par. 2; Fradkin 30,39; Kumar et al. pars. 1-3)
Artificial intelligence can analyze histopathologies for differences in tissues to detect cancer
a feed-forward neural network was 100% effective in diagnosing liver diseases and hepatitis virus
artificial intelligence in diagnostics offers improved accuracy and efficiency in identifying various other conditions such as stroke, skin disease, liver disease, chronic heart disease, and tuberculosis
(Bassani et al. par. 2)
(Kumar et al. par. 3)
(Bassani et al. par. 2; Fradkin 30; Kumar et al. par. 1-3)
TL;DR:
AI can look at imaging and other parameters to diagnose you. This benefit is closely tied to the others.
3. Surgery Assistance
(Kazemzadeh al. 2; Rasouli et al. 557-558; Tangsrivimoet et al. 4)
AI could eventually be combined with other technologies for surgery, so I included some current examples of health tech/ robotics
Health Tech and Robotics
AI
2017
A surgery was first performed by a robot in China (Rebe 45)
AI could assist in in choosing successful surgeries.
(Rasouli et al. par. 557-558),
a decision typically reliant on a surgeon's experience, training, and performance
(Rasouli et al 557-558)
2020
Rwanda sent out robots to help control the COVID-19 virus (Rebe 45)
Artificial intelligence could also predict costs for the patient.
{Rasouli et al. 558)
A woman who could lift a bottle with her robotic arm to take a drink by controlling it with her mind via sensors that measured her brain’s electric pulses (Price par. 18)
AI can predict disease progression through MRIs scans
(Tangsrivimoet et al. 4).
This could eventually reduce the need for invasive tissue sampling, particularly in predicting glioma (a type of brain cancer) progression
(Kazemzadeh et al. 2)
Northwestern University’s Lee Miller placed electrodes into the brains of monkeys
(Price par. 18);
When the monkeys were paralyzed temporarily, they could still move balls and grasp objects, bypassing the blocked nerves
(Price par. 17)
Artificial intelligence outperforms physicians by accurately identifying the affected brain hemisphere 95.8% compared to 66.7% achieved by doctors in temporal lobe epilepsy.
(Kazemzadeh et al. 2).
TL;DR:
Robotics are being used for surgery, and brain measuring devices can help paralyzed people (or monkeys) move limbs with their minds. AI can determine disease area and progression and estimate best surgeries and their costs.
4. Prevents Healthcare Worker Burnout
(Fradkin 29; Stafie et al. 11; Wilton et al 1-12)
The problem:
The solution:
registered nurses (RNs), who make up 59% of the workforce of global healthcare experience burnout at rates between 35% and 45%
(Wilton et al. 2).
artificial intelligence can diminish the strain of administrative tasks, such as by helping fill out electronic health records. Instead of having to sort through tabs, the AI could filter unstructured information
(Fradkin et al. 29).
RN turnover associated costs are estimated at $16,736 per nurse per year.
(Wilton et al. 2).
By freeing up many of the routine tasks, healthcare workers will benefit from being able to focus on more complicated cases and become more efficient.
(Stafie et al. 11)
AI to Predict Burnout
equipping nurses with wearable technology, such as smartwatches, to monitor their physiological changes during shifts (2).
the nurses will be given psychological assessments and integrate patient acuity information (1-12).
estimate cost lost due to decreased productivity from burnout (8).
interventions can be supplied timely (2), as well as assess the causes of healthcare worker burnout (1-12).
TL;DR:
Burnt out healthcare workers cost a lot of money. AI can help burnout by eventually predicting it and clearing up boring tasks.
5. AI Can Make Healthcare more equitable
(Gupta et al. 1814-1816; Malik et al. 6).
the automation of the medical process can greatly impact rural areas or impoverished areas, making healthcare low cost and accessible
(Gupta et al. 1814-1816; Malik et al. 6)
can the quickest routes to rural locations
(Gupta et al. 1816)
make clinical decisions with less resources
(Malik et al. 6)
quickly identify important health issues that affect lower income countries
(Malik et al. 6)
artificial intelligence was able to identify malaria parasites with greater capability than traditional methods by analyzing blood smear images. The AI was also able to estimate parasite density.
(Malik et al. 6)
These tools have also helped India with tuberculosis detection, antibiotic resistance in Brazil, and identifying sickle cell disease in Nigeria.
(Malik et al. 6)
Artificial intelligence has promising potential to provide solutions to many problems with healthcare. Even though there are risks, artificial intelligence’s ability to eventually surpass human-knowledge will aid in the future of humanity and ideally, solve complicated health matters near immediately.
If implemented ethically, it will transform life spans and promote the general well-being by offering resources and promises that could never be made beyond the limitations of conventional capacity.
As we delve deeper into artificial intelligence, it is imperative to ask ourselves what kind of future we are creating; it could be one where healthcare is truly universal and accessible to all, or where existing disparities and inequalities deepen. The trajectory of artificial intelligence in healthcare isn't just about technological advancement, it's about shaping a future where humanity thrives.
Alowais, S.A., et al. “Revolutionizing healthcare: the role of artificial intelligence in clinical practice.” BMC Medical Education, vol. 23, no. 689, 2023, https://doi.org/10.1186/s12909-023-04698-z.
Bassani, Sara, et al. “Artificial Intelligence in Head and Neck Cancer Diagnosis.” Journal of Pathology Informatics, vol. 13, 2022, https://doi.org/10.1016/j.jpi.2022.100153.
Department of Human Health and Services, United States.
Fradkin, Matthew, "Using Artificial Intelligence in Day-to-Day Practice." Contemporary Pediatrics, vol. 39, no. 8, 2023, pp. 27-30, 39. ProQuest, https://ezproxy.saddleback.edu/login?url=https://www.proquest.com/scholarly-journals/using-artificial-intelligence-day-practice/docview/2864891562/se-2.
Fischer, Karen. "The Future of Telemedicine." CQ Researcher, 09 Jun 2023. Thousand Oaks, California: CQ Press, 2023. 12 Mar 2024, doi: https://doi.org/10.4135/cqresrre20230609.
Flo. “About Us.” Flo.Health - #1 Mobile Product for Women’s Health, flo.health/about-flo. Accessed 13 Mar. 2024.
Glazer, Sarah. "The Future of Artificial Intelligence." CQ Researcher, 25 Nov 2022. Thousand Oaks, California: CQ Press, 2022. 21 Feb 2024, doi: https://doi.org/10.4135/cqresrre20221125.
Glazer, Sarah. "Social Media and Youth Well-Being." CQ Researcher, 29 Sep 2023. Thousand Oaks, California: CQ Press, 2023. 13 Mar 2024, doi: https://doi.org/10.4135/cqresrre20230929.
Gupta, Prakamya, et al. “Achieving Health Equity through Healthcare Technology: Perspective from India.” Journal of Family Medicine & Primary Care, vol. 12, no. 9, Sept. 2023, pp. 1814–17. EBSCOhost, https://doi-org.ezproxy.saddleback.edu/10.4103/jfmpc.jfmpc_321_23.
Kazemzadeh, Kimia et al. “Advances in artificial intelligence, robotics, augmented and virtual reality in neurosurgery.” Frontiers in surgery, vol. 10., no. 1241923, 4 Aug. 2023, pp. 01-09, 2, doi:10.3389/fsurg.2023.1241923.
Authors go in depth of health technology in India, focusing on helping rural areas in health equity grow through technological advancements, such as artificial intelligence.
Kumar, Yogesh et al. “Artificial intelligence in disease diagnosis: a systematic literature review, synthesizing framework and future research agenda.” Journal of Ambient Intelligence and Humanized Computing vol. 14, no. 7, 2023, pp. 8459-8486. doi:10.1007/s12652-021-03612-z
Malik, Olatunde O., et al. "Impacts of the Advancement in Artificial Intelligence on Laboratory Medicine in Low- and Middle-Income Countries: Challenges and recommendations—A Literature Review." Health Science Reports, vol. 7, no. 1, 2024, pp. 1-11. ProQuest, https://ezproxy.saddleback.edu/login?url=https://www.proquest.com/scholarly-journals/impacts-advancement-artificial-intelligence-on/docview/2919739219/se-2, doi:https://doi.org/10.1002/hsr2.1794.
McLennan, Stuart, et al. "Embedded Ethics: A Proposal for Integrating Ethics into the Development of Medical AI." BMC Medical Ethics, vol. 23, 2022, pp. 1-10. ProQuest, https://ezproxy.saddleback.edu/login?url=https://www.proquest.com/scholarly-journals/embedded-ethics-proposal-integrating-into/docview/2630533272/se-2, doi:https://doi.org/10.1186/s12910-022-00746-3.
Mehdi, Yusuf. “Announcing Microsoft Copilot, Your Everyday AI Companion.” The Official Microsoft Blog, 15 Nov. 2023, blogs.microsoft.com/blog/2023/09/21/announcing-microsoft-copilot-your-everyday-ai-companion/.
Murdoch, Blake. "Privacy and artificial intelligence: challenges for protecting health information in a new era." BMC Medical Ethics, vol. 22, no. 1, 15 Sept. 2021, p. NA. Gale In Context: Opposing Viewpoints, dx.doi.org/10.1186/s12910-021-00687-3. Accessed 1 May 2024.
Pichai, Sundar. “An Important Next Step on Our AI Journey.” Google, Google, 6 Feb. 2023, blog.google/technology/ai/bard-google-ai-search-updates/.
Price, Tom. "Science and Technology." CQ Researcher, 15 Jun 2013. Thousand Oaks, California: CQ Press, 2013. 26 Mar 2024, doi:https://doi.org/10.4135/cqr_ht_science_and_technology_2013.
Rasouli, Jonathan J., et al. "Artificial Intelligence and Robotics in Spine Surgery." Global Spine Journal, vol. 11, no. 4, 2021, pp. 556-564. ProQuest, https://ezproxy.saddleback.edu/login?url=https://www.proquest.com/scholarly-journals/artificial-intelligence-robotics-spine-surgery/docview/2524178474/se-2, doi:https://doi.org/10.1177/2192568220915718.
Rébé, Nathalie. Artificial Intelligence: Robot Law, Policy and Ethics, BRILL, 2021. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/saddleback-ebooks/detail.action?docID=6697085.
Stafie, Celina Silvia, et al. “Exploring the Intersection of Artificial Intelligence and Clinical Healthcare: A Multidisciplinary Review.” Diagnostics (2075-4418), vol. 13, no. 12, June 2023, p. 1995. EBSCOhost, https://doi.org/10.3390/diagnostics13121995.
Tangsrivimol, Jonathan A et al. “Artificial Intelligence in Neurosurgery: A State-of-the-Art Review from Past to Future.” Diagnostics (Basel, Switzerland) vol. 13,14 2429. 20 Jul. 2023, pp. 1-33. doi:10.3390/diagnostics13142429.
Turing, A.M. “Computing Machinery and Intelligence”, Mind, Volume LIX, Issue 236, October 1950, Pages 433–460, https://doi-org.ezproxy.saddleback.edu/10.1093/mind/LIX.236.433
Wilton, Angelina R., et al. “The Burnout PRedictiOn Using Wearable aNd ArtIficial IntelligEnce (BROWNIE) Study: A Decentralized Digital Health Protocol to Predict Burnout in Registered Nurses.” BMC Nursing, vol. 23, no. 1, Feb. 2024, pp. 1–14. EBSCOhost, https://doi-org.ezproxy.saddleback.edu/10.1186/s12912-024-01711-8.
Worsfold, Lauren et al. “Period tracker applications: What menstrual cycle information are they giving women?” Women's health (London, England), vol. 17, 2021, n.p., National Library of Medicine. doi:10.1177/17455065211049905.
Zhaunova, Liudmila et al. “Characterization of Self-reported Improvements in Knowledge and Health Among Users of Flo Period Tracking App: Cross-sectional Survey.” JMIR mHealth and uHealth, vol. 11 e40427. 26 Apr. 2023, doi:10.2196/40427.