The Role of Artificial Intelligence

in Healthcare
< Foundation English >
# 25/05/2025
K.Ravindu Chandana

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 What is Artificial Intelligence?

• AI is the ability of machines to perform tasks that typically

require human intelligence.

• Key areas include: machine learning, natural language

processing, robotics, and computer vision.

• In healthcare, AI helps analyze data, diagnose diseases, and

support clinical decisions.

Robotics
Artificial Intelligence

Computer Vision

Machine Learning

Natural Language Processing

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 Why AI is Important in Healthcare

Helps doctors Saves time and

work faster and money
better

24/7 Virtual
Gives better Health
care to patients Assistants

Reduces human
Personalized
errors
Treatment Plans

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 How AI is Used in Healthcare

Predective Modeling Virtual nurses

(chatbots)
Forecasting patient outcomes
Supporting patients and
providers
Medical imaging
Enhancing the interpretation
of images 4
 Advantages of Using AI

Faster Diagnosis Saves Time and Money

AI gives test results quickly and helps doctors AI helps doctors finish tasks faster, which saves
make fast decisions. hospital costs.

Better Accuracy 24/7 Availability

AI makes fewer mistakes than humans when AI chatbots and tools work all the time — even

reading scans or reports. at night.

Early Disease Detection

Personalized Treatment
AI can find diseases before they get worse (like cancer
AI gives treatment plans based on each patient’s health
or heart problems)..
data.
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 How AI Helps in Medical Scans

AI in Radiolog Early Cancer Detection AI-Powered Chatbots

• AI tools analyze X-rays and • AI detects signs of breast, skin, and • Chatbots like Babylon Health or
MRIs with high accuracy. lung cancer earlier than traditional Ada can:
• Helps radiologists detect methods. • Ask questions
abnormalities faster. • Example: MIT AI system detects breast • Analyze symptoms
• Reduces human error and cancer 5 years before symptoms. • Give possible conditions
saves time. • 94.5% accuracy in AI-assisted • Available 24/7 and support
mammogram reading (vs. 88% by patients in remote areas.
human alone).

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 Benefits of AI in Healthcare

Improved Accuracy & Reduced Human Error Cost Savings & Resource
Faster Service Delivery
Efficiency Optimization

• AI systems process large • AI tools reduce mistakes • Automates routine tasks • Virtual assistants handle
datasets faster than caused by fatigue or like documentation or symptom checks 24/7.
humans. oversight. triage. • Faster diagnostics
• Helps detect patterns in • Alerts doctors to • Fewer unnecessary tests reduce patient wait
imaging, lab results, and overlooked symptoms or or misdiagnoses reduce times.
patient records. medication conflicts. hospital costs. Example: AI chatbots
Example: AI in radiology Example: Clinical Decision • Predictive analytics help triage patients before they
achieves up to 94%+ Support Systems (CDSS) manage staffing, see a real doctor.
accuracy in diagnosis. flag potential drug equipment, and budgets
allergies. better. 7
 Real-Life Examples of AI in Healthcare

Case 1: AI Diagnosed Rare Condition Missed

Case 2: AI Helped Detect Thyroid Cancer
by 17 Doctors

Woman misdiagnosed with acid reflux &

4-year-old boy suffered pain & motor issues.
arthritis.
Visited 17 doctors—no clear diagnosis.
Used ChatGPT to analyze her symptoms.
Mother used ChatGPT with MRI notes.
Suggested thyroid issue ➜ led to testing.
ChatGPT suggested Tethered Cord Syndrome.
Diagnosis: Hashimoto’s disease + Cancer.
Diagnosis confirmed by doctors—surgery
Life-saving surgery performed.
successful.

"These real-life stories show how AI, especially ChatGPT, is transforming

diagnosis. In the first case, 17 doctors couldn't identify a rare neurological condition in a
child, but ChatGPT offered the correct suggestion, which was later confirmed.
In another case, a woman used AI to help uncover thyroid cancer that was initially
missed. These examples highlight how AI can support—not replace—medical
professionals, especially in complex or rare situations."
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 Challenges and Limitations of AI in Healthcare

“AI is powerful, but it comes with serious challenges. First, there’s the risk of data leaks
— we must protect patient privacy. Second, AI can show bias if it’s trained on limited or
unfair data. It also lacks transparency, meaning we often don’t know how it made a
decision. Lastly, implementing AI is expensive. Not every hospital or clinic can afford it.
So while AI helps us, we must use it carefully and ethically.”

Data Privacy and Security Concerns Algorithm Bias and Lack of Transparency High Implementation Cost

❖ Patient data is vulnerable to leaks ❖ AI can misdiagnose due to biased data. ❖ AI systems need costly
or hacking. ❖ Many AI systems are “black boxes” with development and upkeep
❖ Compliance with regulations like unclear decisions. ❖ Smaller hospitals may not
GDPR is essential to safeguard ❖ This reduces trust and accountability in afford this technology.
medical records. healthcare. ❖ High cost risk increasing
❖ Protecting patient confidentiality healthcare disparities.
builds trust and ensures legal
compliance.
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 Conclusion

Summary of Key Points

o AI improves healthcare efficiency and accuracy

o Risks include bias, privacy concerns, and high costs
o Ethics and access must be patt of the conversation

Final Thoughts

o Innovation should not come at the cost of trust or equity

o Ethical freameworks and transparency are essential
o Human oversight remains crucial in decision-making

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 References

[1] E. Topol, Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again. New York, NY, USA: Basic Books, 2019.

[2] NHS England, "AI in Healthcare," NHS England, 2023. [Online]. Available: https://www.england.nhs.uk/aiforhealthcare/ [Accessed: May 25, 2025].

[3] World Health Organization (WHO), Ethics and Governance of Artificial Intelligence for Health. Geneva: WHO, 2022. [Online]. Available:

https://www.who.int/publications/i/item/9789240029200 [Accessed: May 25, 2025].

[4] University of Chicago, "The Mere Presence of Your Smartphone Reduces Brain Power," UChicago News, 2020. [Online]. Available:

https://news.uchicago.edu/story/mere-presence-your-smartphone-reduces-brain-power [Accessed: May 25, 2025].

[5] Common Sense Media, "The Common Sense Census: Media Use by Tweens and Teens," 2019. [Online]. Available:

https://www.commonsensemedia.org/research/the-common-sense-census-media-use-by-tweens-and-teens-2019 [Accessed: May 25, 2025].

[6] BBC News, "The Social Media Addiction That Cost Me My Degree," BBC News, 2023. [Online]. Available: https://www.bbc.com/news/world-asia-66120393

[Accessed: May 25, 2025].

[7] World Health Organization (WHO), Digital Technologies: Shaping the Future of Primary Health Care. Geneva: WHO, 2021. [Online]. Available:

https://www.who.int/publications/i/item/9789240024892 [Accessed: May 25, 2025].

[8] Harvard Business Review, "Artificial Intelligence in Health Care: Anticipating Challenges to Ethics, Privacy, and Bias," HBR, 2020. [Online]. Available:

https://hbr.org/2020/10/artificial-intelligence-in-health-care [Accessed: May 25, 2025].

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Thank You . . . !

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