Medical Testing Infographic

AI in Medical Testing

Ava Dalen

Impacts

Data Privacy

The protection of patient health records to protect patient's autonomy, build trust with the physician, and use data to advance medical practices without impacting the patient.

Personalized Treatment Plans

Cons

Pros

• Loss of Human Interaciton that patients need
• Biases occur depending on how the AI was trained
• Ethical Questions
• Expensive to program and run

• Accurate Medical Imaging
• AI Powered Surgical Assitants
• Online Chatbots that can assist patients when physcians aren't available
• Administrative Task Assistance

Basing how a patient is cared for on their medical history, genetic information, and their lifestyle.

Future Thoughts

This technology is very promising and will be incredibly helpful to the healthcare field if it's current problems can be solved. Otherwise, I believe that it might be more detrimental than good.

How AI is used in Data Privacy

• Monitors systems for anomalies and abnormalities
• Identifies patterns in data activity for threats
• Deidentify classified patient information (take out all information that would make the patient recognizeable from their case)
• Monitor who has access to specific cases

How is AI Used in Treatment Plans

• Processing data from patient records, family health, and anywhere else.
• Prediction of patient responses
• Can cycle through and pick the best option

AI Cons

Personalized Treatment Plans

• Could be unequal treatments between patients
• Privacy concerns
• Potential for a misdiagnosis
• Ethical dilemmas (if something goes wrong, is the AI or the physician wrong)
• Physcians have to disclose the use of AI to their patients and get approval
• the data might be biased towards certain genders or races
• Can create an over reliance on AI since these can be done by physcians, they just take longer

AI Pros

Data Privacy

• Cost reductions
• Can find data breeches faster than human employees
• Continuously able to adapt to new challenges and threats rather than having to learn or work with a team

AI Cons

Data Privacy

• Data can be leaked (it doesn't know HIPPA)
• Can be cyberattacks since AI is connected to networks
• Biases might cause it not to know what data to keep private

AI Pros

Personalized Treatment Plans

• Patient-specific therapies
• Care based on all available data of genetics, hospital tests, and lifestyle
• Cost reductions
• Faster because it can adapt to health changes in seconds
• Can monitor 100% of time, unlike physcians
• Increased engagement for patient and health team
• Descisions-making improves for physcians because they have data-driven consulters

Sources

Nicholson Price, Problematic Interactions Between AI and Health Privacy, (2021).https://doi.org/10.26054/0d-th4e-sgvq

Dimitt, Kyle. “Artificial Intelligence – A Danger to Patient Privacy?” (August 28, 2023). Exabeam.https://www.exabeam.com/blog/infosec-trends/artificial-intelligence-a-danger-to-patient-privacy/

Hill, Tiana. “Data Privacy and Protection in AI for Precision Medicine” (October 31, 2023). TheREPROCELL Blog. https://www.reprocell.com/blog/data-privacy-and-protection-in-ai-for-precision-medicine

Singleton, Nicole. “AI in Medicine: Transforming Patient Treatment and Care” (October 28, 2024).Healthcare & AI. https://www.thoughtful.ai/blog/ai-in-medicine-transforming-patient-treatment-and-care#:~:text=AI%2Dpowered%20systems%20generate%20personalized,the%20likelihood%20of%20adverse%20effects

Nasim, Sadat M., and Filipe S. Manuel. "Enhancing Clinical Decision Support for Precision Medicine: AData-Driven Approach." Informatics, vol. 11, no. 3, 2024, pp. 68. ProQuest,http://ezproxy.wartburg.edu/login?url=https://www.proquest.com/scholarly-journals/enhancing-clinical-decision-support-precision/docview/3110480307/se-2,doi:https://doi.org/10.3390/informatics11030068

Examples: Lab Testing: Urine, BloodImage Testing: CT Scans, MammogramsBiopsiesGenetic TestingPhysical ExamsEndoscopy: Colonoscopies, Bronchoscopies

What is Medic Testing?

How hospitals/clinics are able to detect, diagnose, and/or monitor diseases and conditions

I believe, in the future, a way to make sure the AI keeps things confidential will be developed. This could be done through retraining the systems or doing a system check after a patient’s case is closed and before another one is introduced to make sure nothing is crossed or shared.

I think using AI in the medical field definitely needs more work before it is considered a necessary tool, but it will eventually get there and, hopefully, help medicine run very smoothly and effectively.

If the full potential of this is reached, medical testing will become a lot faster of a process and one that is more efficient. Waiting for tests to be analyzed or analysis inaccuracies hopefully won’t exist so treatments can be done even faster and less disease-related death will occur due to it.