I have chosen this industry because it plays a huge role in impacting people's quality of life and I am very interested in learning how AI will transform the healthcare industry and how it can continue to improve its services. My interests lies in how we can leverage AI to close and fix the current gaps in healthcare like affordability and accessibility as well as creating a more patient centric system to improve outcomes and solutions. I believe as technology continues to evolve, it should also improve quality of live and make our lives efficient and provides opportunities and possibilities that are once hard to attain.

In this Padlet wall, I will cover examples of AI Usage and Applications in the healthcare industry, discuss future trends and ethical considerations, societal impacts of AI in healthcare like employment, privacy etc as well as sharing my personal reflections and thoughts about the topic regarding to the research process, challenges and what I have learned.

The technology it utilizes is deep learning algorithm. Deep learning algorithms are trained with large data sets is capable of recognizing complex patterns and features that can go unnoticed by the human eye. With deep learning algorithms, it enhances medical imaging techniques abilities to provide more accurate and efficient disease diagnosis, which enables early abnormalities detection (tumors, cancer, degeneration etc), predicting disease outcomes and providing better treatment plans and insights for the patients and rheumatologists healthcare providers.

With all its benefits AI in medical imaging provides, there are challenges as well. First, it is very costly to set up during the initial set up process For the AI model to be effective, it also needs large, diverse and high quality data that can be difficult to collect and standardized.

https://images.app.goo.gl/9pQ1kaVuSCEnyiqQ7

I find this very interesting because to me it means more people will be able to have accurate and quicker diagnosis and better treatment plans. This means people are able to treat their diseases faster as well as preventing detrimental effects before it is too late. In my opinion, this is a good thing as it can prolong people's lives and ensuring high quality services.

The technology it utilizes is computer vision and image recognition. With its abilities to process large data, it proven its capabilities of analyzing biological systems, simulate drug-target interactions as well as predicting the safety and efficacy of drug candidates. This allows better clinical trials simulation and therefore accelerating and improvement the drug development process.

There are some limitations and challenges that comes with it as well. Similarly to medical imaging, it requires high quality training data for it to be effective and it can be costly to attain and can be very hard to acquire, especially pertaining to rare diseases. The data also has to be bias and error free or it will lead to inconsistent results, reduced reliability which can hinder the development trials. To this day, there has been no AI-developed drug in the market yet.

https://images.app.goo.gl/TFtS1njqkANh2WMM9

I find this very interesting because I find it very fascinating how drugs can be created by AI or at least developed by AI. I can not wait to see how far it can reach and what type of drugs it can develop and what diseases it can cure. I also find it very concerning as I wonder if speeding up the clinical trials means better drugs or faulty drugs.

All of this is possible due to machine learning. By analyzing large complex data sets, like patients characteristics and past surgeries, it can provide better information and decisions about risks and benefits of certain surgeries. Another major technology is computer vision, and by recognizing patterns, images and processing digital videos and images, it can predict what may happen and provide additional oversight during the surgery through recommendations and decision support.

There are some limitations and challenges as well like accountability. Who is at fault if the AI assisted surgery leads to a bad outcome, is it the hospital, the surgeon, or the AI? Another limitation is data limitation and bias, where limited database can lead to bias conclusions. If the AI is fed with information on a certain demographic or population's information, its decisions may not accuracy apply to another.

https://images.app.goo.gl/8vw4sxkrm5fHGgGW6

I find this very interesting because the idea of robots assisting in surgery is very scary yet cool to think about. This means AI and robots will be able to perform surgical procedures one day as they evolve. Currently they are already able to perform simple tasks like stitches and tying a knot. Like mentioned before, if there is a bad surgery with AI involvement, who is held accountable? I feel like this is a very important factor to consider before fully utilizing AI in surgical practices.

There are also some ethical considerations that is needed to be addressed. First, data privacy, with AI requiring large amounts of data, it also means it is prone to cybersecurity attacks. Healthcare providers and companies must ensure and comply to strong data protection regulations to protects its patients' privacy and system security. Another ethical consideration is consent, patients should notified about the use of AI in their treatments and diagnosis if any as well as having the options to opt out if patients feels uncomfortable or prefers traditional services. Another is bias, the information used to train the AI should be standardized to mitigate biases and errors to ensure it provides equal treatments for all patients and prevent misdiagnosis and mistreatments.

I am excited to see what AI can do to help the healthcare industry and how it can close the healthcare accessibility and affordability gap. AI can provide many innovations to the industry and change people's lives. Healthcare regulators should have regulations ands framework on data privacy and security to protect their patients. A weak system security will lead to data breaches, misuse of patient's information from cyber criminals, which I feel is an important concern to consider.

Another societal impact is rapid treatments and urgent detections. With AI, patients can receive fast life saving treatments before disease can cause any life threatening issues and physicians and clinicians will be able to provide quick consultations and diagnosis for their patients, with AI highlighting early on abnormalities and risks pertains to the individuals.

Overall, I see these societal impacts as benefits to the industry. If AI is able to alleviate the stress, the workload and help with the growing patients, I see it as an opportunity for the healthcare industry to grow and evolve. Its massive benefits for the healthcare workers and patients will only help the industry in the long run and as long there is proper conduct and regulations, AI is an awesome tool and addition to healthcare.

[Rationale: This article provides a detailed discussion of possible future trends in healthcare.]

Future of AI in medical imaging: Challenges and opportunities - Quibim. (2024, December 13). Quibim Website. https://quibim.com/news/ai-in-medical-imaging/

[Rationale: This article talks about the limitations and challenges of AI use in medical imaging.]

jaime. (2021, June 28). The Social Impact of Artificial Intelligence (AI) on Healthcare. Healthcare AI | Aidoc Always-on AI. https://www.aidoc.com/learn/blog/social-impact-artificial-intelligence/

[Rationale: This article provides and discusses possible societal impacts of AI technology in healthcare.]

McCartney, J. (2023, June 7). AI Is Poised to “Revolutionize” Surgery. ACS; American College of Surgeons. https://www.facs.org/for-medical-professionals/news-publications/news-and-articles/bulletin/2023/june-2023-volume-108-issue-6/ai-is-poised-to-revolutionize-surgery/

[Rationale: This article talks about AI technology and how it is currently used in surgery and how it can continue to evolve in its capabilities.]

Overview: AI in the Healthcare Industry. (2023, November 13). Hitrustalliance.net. https://hitrustalliance.net/blog/overview-ai-in-the-healthcare-industry

[Rationale: This article provides a detailed overview of AI and its role in the healthcare industry and system as well as ethical considerations needed to be addressed.]

Pinto-Coelho, L. (2023). How Artificial Intelligence Is Shaping Medical Imaging Technology: a Survey of Innovations and Applications. Bioengineering, 10(12), 1435. https://doi.org/10.3390/bioengineering10121435

[Rationale: This article talks about AI and how it is used in medical imaging, which is very helpful in learning about AI's capabilities in medical imaging.]

Zhang, K., Yang, X., Wang, Y., Yu, Y., Huang, N., Li, G., Li, X., Wu, J. C., & Yang, S. (2025). Artificial intelligence in drug development. Nature Medicine, 1–15. https://doi.org/10.1038/s41591-024-03434-4

[Rationale:This article talks about AI and how it can be used to improved drug development trials.]