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In this Padlet wall, we will be exploring AI in healthcare.  Artificial Intelligence plays important role in healthcare field. AI algorithm can help analyzing medical images, laboratory result, and detecting tumors. I chose this industry because my mother was a doctor. I spend most my life in the hospital before the age of 10. I was sitting in the office or playing around in the hospital. I am interested in exploring the accuracy of AI diagnoses and the risks associated with AI-generated personalized treatment plans. In this wall, I would be exploring how AI make a difference in healthcare field. How AI diagnoses process is different from human diagnoses. How AI can help patients with personalized treatment plans. How AI can help monitoring patient. My parents are the type of people who don’t like to go to the hospital because they must ask for permission from their boss. They frequently suffer from health issues like stomach aches, muscle soreness, and dizziness. My mom tends to determine the cause based on what she has encountered before, though her assessments might not always be accurate. For instance, when I had persistent headaches after playing basketball, my mom always assumed it was due to lack of sleep. However, after a medical check-up, the doctor found that it was due to poor posture, playing basketball gives more pressure to my neck and shoulders later led to having a headache. With AI machine/Virtual health assistant, it would save a lot of time diagnose simple symptoms at home using diagrams or videos for people who does not have time to go to the hospital. For elderly individuals like my grandparents who are suspicious that they will get sick, with AI tracker, it will reduce a lot of confusion.

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Google DeepMind is an artificial intelligence system that was trained by medical professionals to detect diseases, cancers, and tumors. The DeepMind mainly relies on machine learning technology to learn from the previous research paper, experience from professionals, and large set of testing. DeepMind is a significant improvement in the medical field. One example would be the breast cancer screening trial, around 29,000 abnormal x-ray images was scanned by DeepMind, and only 5.7% of false positives result and 9.4% of false negatives result (Kimball). The purpose of this system is to have “faster diagnosis and developing life-saving treatments.” (Regalado). This system can definitely help the shortage of medical professionals and save a lot more lives. However, this system also has privacy concerns and ethical concerns. AI system needs a lot of personal data as a base for accurate diagnosis. Your personal data will be collected by the AI and use for future reference. One concern would be: will your medical history be leaked to save another person’s live? Another concern is the biasness of the Ai system. Since the AI is trained by human and learning from large dataset. Will the AI make unfair or bias decision? I think the ethical and privacy issue really matters here. Patient should be allowed to choose whether they agree to be diagnosed by the AI system. Similar to application consent that if patient choose to opt-in, that means they agree to have their personal data be collect and use. If opt-out, doctors should respect the patient’s decision and not provide their personal data to the AI system.

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In this video, you will understand what is Google DeepMind, and how professionals train it through machine learning.

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Detecting cancer in real-time with machine learning

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IBM WATSON for Oncology | Upgrading Cancer Care | Manipal Hospitals India

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Future Trends and Ethical Considerations

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Future Trends and Ethical Considerations

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AI in healthcare is definitely going to make significant improvement. As we see in the wall post of Google DeepMind, WFO, and GE Healthcare Mural. We can see the potential that AI has in healthcare field. AI can improve that accuracy and speed of diagnosing a cancer; Providing suable or personal treatments, manage tasks and workflow based on the condition, and help doctors with their research and development (Los Angeles Pacific University). AI will continue to improve in the accuracy of diagnosing, increase safeness of treatment, reduce human error, and help to relieve the pressure of shortage of doctors. In the example of COVID_19 pandemic, if we can use AI tool as a source to compare with other viruses exist before to develop treatment. Similar to the analyzing cancer image, we can train the AI to diagnose the virus and design treatment for people, then We could save a lot of peoples live. However, there are ethical concerns. Whether the people who train the AI have bias research result, which led to incorrect decision making of AI. There are also privacy concerns that if AI leaks people’s information, whether the security system is strong enough to protect attacks from hackers. I think the most important issue here for AI is who should be responsible for the false or incorrect diagnose or treatment. If a patient die because of false diagnose, should the people who train the AI be responsible or the doctor that use the AI.

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Watson for Oncology is an artificial intelligence system that developed by IBM Watson Health to help doctor to prompt recommended treatment for cancer patients. Watson for Oncology can use natural language processing to data, it also uses cloud-based supercomputer to digest large amount of data(Ross and Swetlitz). WFO really build the bridge between large data and doctors. It increases the efficiency of treatment. Doctors do not have to spent large amount of time to read research papers or medical documents. However, “ several doctors said Memorial Sloan Kettering’s training injects bias into the system, because the treatment recommendations it puts into Watson don’t always comport with the practices of doctors elsewhere in the world"(Ross and Swetlitz). Based on my reading, the WFO is not yet mature, there are cases that the result is not accurate or suable for patient. I think WFO needs more testing case, whereas right now, not all hospital use WFO and agree to give the patient information to the database.

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GE Healthcare Mural is a software that utilize artificial intelligence to help doctors monitor patient’s health condition. The key feature is it can follow hospital’s protocols and provide doctors warning of patients that need prioritize treatment. GE Healthcare Mural mainly uses machine learning to learn about the hospital’s protocols and analyzing patient’s data. It also uses cloud computing to process real-time data for patients. GE Healthcare Mural was used during the pandemic of COVID-19. Hospital was facing extreme demands on clinical resources and pressure of shortage on doctor units. With the help of Mural, hospital provide much more affordable and high quality treatment to the patient(“GE Healthcare Deploys Remote Patient Data Monitoring Technology to Help Clinicians Support Most Critical COVID-19 Patients across the Health System”). I think GE Healthcare Mural is a great tool that hospital can use for efficient treatment and monitoring patient health condition. The only concern is the privacy issue since the Mural tracks and analyze patients’ data. There is a risk of cyber leaks.

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After reading multiple documents and research paper, where there are good and bad about AI in healthcare. Case-study research result varies. On one hand, AI can significantly decrease human error and providing faster accurate diagnose result. One the other hand, AI system needs human research result and large data that supports its decision-making. All the research are from human, if there are any bias in the algorithm that can led to AI making inequitable treatment. As of right now, AI is still a double-edge sword. Similar to when internet is first created, it connects people together but also led to cyber-crimes. Without proper laws and regulations, if by any chance,  I think I would not agree to let my doctor diagnose me with the help of AI.

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Enough though AI brings a lot of benefits in term of diagnosing, monitoring patients, and designing treatments. It also brings significant challenges to the society. In terms of employment, AI can reduce the pressure of lack of health professionals(Alowais et al.). Assisting doctors to make faster and more accurate diagnoses based on data. It can also reduce the time of doctors doing redundant works, so they can focus on save lives. However, the downside is that job displacement. A simple example would be if a hospital needs 4 professionals in a cancer department to help diagnosing cancer, with the help of AI, there might only needs only 1 professional that supervise it. But it also creates AI expertise job positions that might be unfair for current medical students. In term of privacy issue, AI system needs large set of data to support the conclusion. That means AI will connects data from the patients, maybe along with family histories. Even though AI can be trained to detect cyber-attacks, but at the same time, cyber criminals can use AI to advance their skill. There is a chance that patient information is leak because it is store in cloud. In term of ethical concerns as I mentioned before, should AI be allowed to make decision that regard a people’s life? Who should be responsible for the decision? I think the patient should have the right to choose whether they want the doctor to use AI in their treatment or diagnose process. Consent form should be clear and well stated on who is responsible for false decision-making.

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Introduction and Google DeepMind

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Kimball, Whitney. “Google’s AI Proves Better at Detecting Breast Cancer than Doctors.” Gizmodo, 2 Jan. 2020, gizmodo.com/googles-ai-proves-better-at-detecting-breast-cancer-tha-1840773871. Accessed 14 Mar. 2025.

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Regalado, Antonio. “DeepMind Is Using AI to Pinpoint the Causes of Genetic Disease.” MIT Technology Review, 19 Sept. 2023, www.technologyreview.com/2023/09/19/1079871/deepmind-alphamissense-ai-pinpoint-causes-genetic-disease/.

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“GE Healthcare Deploys Remote Patient Data Monitoring Technology to Help Clinicians Support Most Critical COVID-19 Patients across the Health System.” BioSpace, 15 Apr. 2020, www.biospace.com/ge-healthcare-deploys-remote-patient-data-monitoring-technology-to-help-clinicians-support-most-critical-covid-19-patients-across-the-health-system. Accessed 14 Mar. 2025.

Ross, Casey, and Ike Swetlitz. “IBM Pitched Its Watson Supercomputer as a Revolution in Cancer Care. It’s Nowhere Close.” STAT, STAT, 5 Sept. 2017, www.statnews.com/2017/09/05/watson-ibm-cancer/.

Alowais, Shuroug A, et al. “Revolutionizing Healthcare: The Role of Artificial Intelligence in Clinical Practice.” BMC Medical Education, vol. 23, no. 1, 22 Sept. 2023, bmcmededuc.biomedcentral.com/articles/10.1186/s12909-023-04698-z, https://doi.org/10.1186/s12909-023-04698-z.

Los Angeles Pacific University. “Revolutionizing Healthcare: How Is AI Being Used in the Healthcare Industry?” Los Angeles Pacific University, Los Angeles Pacific University, 21 Dec. 2023, www.lapu.edu/ai-health-care-industry/.

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