AI in Healthcare by Houston Vysniauskas

Personal Overview

justasvysniauskas — 2025-03-13 03:40:59 UTC

My personal overview on why I chose healthcare as an industry role for AI. And one of the main reasons is because AI in healthcare has played a huge role. Eventually, this will take a very huge shift on how we vision on healthcare. It’s very significant because it had the capacity to have plans such as treatments. To have an early detection for diseases. Though, the main purpose for AI is to make it more efficient. However, AI is used extensively in medical sciences. Common applications include diagnosing patients, end-to-end drug discovery and development, in a result, improving communication between physical and patient, transcribing medical documents. Great advances have been made in using artificial intelligence. It is also capable of classifying skin cancers with a level of competence comparable to dermatologist. Additionally, AI can reduce human error in healthcare by automating tasks and decision support. This technology is drastically improving, AI in hospitals and other healthcare systems can become smarter, faster, and more efficient in providing care for many people worldwide. It’s turning out, it would be transforming how patients receive quality care while mitigating costs for providers and improving health outcomes. Because the main purpose of using AI is primarily utilized to increase speed and accuracy in the healthcare realm. Although, there are disadvantages about the ethical concerns and data privacy issues. As a result of potential job displacement and challenges. And the reliability and trust issues in AI-driven decision making. Though AI is still significant in healthcare.

X-ray image analysis AI

justasvysniauskas — 2025-03-13 03:41:05 UTC

AI healthcare apps support radiologists with decision making and give them more time to interact with patients. This way, doctors can handle more cases in a day. The benefit would give a better diagnosis. In a result these X-ray models have been found to be more effective such as lung cancer detection can be improved by using X-ray AI, and also has outperformed radiologists in detecting tuberculosis. The limitations of X-ray image analysis by AI, is that it is a result of data quality, as a result of that almost all AI algorithms lack the robustness recommended for clinical use.

Personal thoughts ) The reason why I found this interesting is because X-ray is because one of the reasons is because it improves the accuracy and efficiency for some forms of diagnosis, though the input is that it would improve better images too. The potential impact, the main purpose of the X-ray analysis powered by AI, is making faster results and also to reduce workload and it includes by improving patient care. My opinion on the X-ray analysis powered by AI is that it is very impressive, and I do believe that having a faster diagnosis would eventually help both to save lives and take immediate action.

Diagnostic AI

justasvysniauskas — 2025-03-13 03:41:13 UTC

Diagnostics based on AI and ML provide medical professionals with accurate data analysis to detect patterns and dependencies. As medical staff get real-time insights which gives the opportunity to support or question their treatment decisions. Traditional diagnostic methods often rely on the subjective interpretation of medical professionals, such as variability. AI can reduce variability by providing data-driven insights, leading to more reliable diagnosis. Machine learning helps to structure and use this information for more precise diagnosis and scientific research. The challenges result of lack of standardization in imaging and diagnostic protocols. It can be biased and lead to disparities in healthcare outcomes for certain patient populations.

Personal thoughts ) I found this interesting because I never heard of Diagnostic AI and I don’t know what it is. Though I do find Diagnostic AI interesting because it does have similarities such as the X-ray analysis powered by AI. Although, the Diagnostic AI has an impact such as having the healthcare resource and reducing costs. Additionally, there is also a negative impact of Diagnostic AI would be data bias, or in other words incomplete data. My thoughts on this is that it's a new discovery, but I'm pretty sure there is more to understand. I think that Diagnostic AI is a good use in healthcare.

Alert Management

justasvysniauskas — 2025-03-13 03:41:17 UTC

AI - powered alert management in healthcare is revolutionizing how doctors respond to patient health changes. AI smart alerts to help analyze patient data in real-time and recognize risks before they become serious problems. The benefit of Alert management is the ability to detect and address threats before they escalate into significant security incidents. It also helps to reduce alert fatigue by filtering out noise and ensuring that security focuses on the most crucial issues. The limitations on Alert Management, poor alert configuration, overly sensitive thresholds trigger an excessive number of alerts, inadequate staffing, alert fatigue often stems from not having enough staff or resources dedicated to cybersecurity.

Personal thoughts ) I found Alert management interesting even though I wasn’t aware that it helps to detect threats. But it also enables healthcare providers to respond to patients' needs and challenges. Though without Alert management, this would affect the teams and it would lead to non-critical alerts, and missed issues. Alert management almost played the same role as cybersecurity. Though it can identify potential breaches, and would take action to prevent data loss or damage. I do find alert management interesting because alert management has more diverse tasks in order to address anything that poses a threat, yet I do believe alert management is very crucial in healthcare.

Future Trends and Ethical considerations

justasvysniauskas — 2025-03-13 03:46:29 UTC

One of the future trends and potential developments of AI in healthcare. AI will extract important information from a patient's electronic footprint. Though, it also improves outcomes for both patients and clinical teams, lowering healthcare costs, and benefiting population health. AI could automatically prepare the most important risks and actions given a patient's clinical record. AI- based systems will also bring specialist diagnostic expertise into primary care. With the use of Ai in everyday life, the impact can be significant. It's imperative that devices and products which harness the power of AI, and the way the data is used to train them, are regulated and compliant, to protect privacy and data, ensure products are suitable for all users, and keep everyone safe. The rapid advancement of technology, as in the result of regulations can lag behind the products and devices they need to regulate. AI itself can be used to speed up this process, to ensure quality and compliance, help organizations analyze the large amounts of data needed for verification and validation, help them be ready for regulators and auditors, and assist in the delivery of their products to patients. Informed consent is a fundamental ethical principle in healthcare, and its importance extends to AI applications. The future for AI in healthcare would eventually see a major change in the fields of healthcare. I think it is very important to address that the use of AI in healthcare is not a bad idea, but they should not depend on it too much on AI.

Societal Impact

justasvysniauskas — 2025-03-13 03:52:38 UTC

The societal impact of AI being used in healthcare is more effective and incredibly significant. There is a huge social change that disrupts the way we live in the human community. Unemployment is because many workers will be replaced by machinery. Wealth inequality will be created as the investors of AI will take up the major share of the earnings. New issues surface not only in a social sense but also in AI itself as the AI being trained and learned how to operate the given task can eventually take off to the stage that humans have no control. The human masters who create AI may invent something that is racial biased or egocentrically oriented to harm certain people. There are several immediate ways, such as practitioner wellbeing and support. The hard reality of medical care today is that it's busy, demanding, stressful and other overwhelming. Practitioners are under constant pressure to deliver exceptional care while juggling exceptional workloads. A patient may have immediate, life-saving treatment prior to a stroke taking full effect. Rapid diagnosis and urgent detection, as AI has become increasingly sophisticated across multiple use cases, particularly in stroke detection. As a result, the patient may have immediate, life-saving treatment prior to a stroke taking full effect. Improved radiology capabilities, solutions such as Aidoc have been on the market for long enough to prove their value by providing radiologists with essential support. As for the societal impacts of AI being used in healthcare. It does demonstrate this intelligent tool can support the amount of work.

Reflection

justasvysniauskas — 2025-03-13 03:56:22 UTC

This is one of the most interesting moments in healthcare. It's very satisfying to see how much development has brought, which would revolutionize healthcare. I think it’s essential to understand that so many varieties of AI are being used. However, it's believed that we must remain cautious about AI in healthcare. I have learned that AI in healthcare is one big step of efficiency. Eventually, robots or AI will be used to help patients even more, such as those who can’t walk or are feeling ill. I believe there will be more technology in hospitals, such as AI. But this is one huge step of development.

Citations

justasvysniauskas — 2025-03-13 03:59:51 UTC

1.Artificial Intelligence (AI) in Healthcare & Medical Field. ForeSee Medical. (n.d.). https://www.foreseemed.com/artificial-intelligence-in-healthcare

2.Revolutionizing Healthcare: How is AI being used in the healthcare industry?. Los Angeles Pacific University. (n.d.). https://www.lapu.edu/ai-health-care-industry/

3.Shpachuk, A. (2025, March 7). Top 12 real-world artificial intelligence (AI) applications in Healthcare. Empeek. https://empeek.com/insights/top-ai-applications-in-healthcare/#post-nav-0

4.AI in X-ray analysis: Benefits & Challenges in 2025. (n.d.). https://research.aimultiple.com/xray-ai/

Shah1, R. M., Gautam2, R., Z, A., S, R., M, Z., J, A.-G., J, S., DR, A., D, E., S, L., O, T., WD, W., P, R., Office of the Assistant Secretary for Planning and Evaluation, D, G., F, D. B., S, J., S, N., W, P., … S, O. (2023, October 19). Overcoming diagnostic challenges of artificial intelligence in pathology and Radiology: Innovative Solutions and Strategies. Indian Journal of Medical Sciences. https://ijmsweb.com/overcoming-diagnostic-challenges-of-artificial-intelligence-in-pathology-and-radiology-innovative-solutions-and-strategies/

5.Porter, A. (2025, February 11). Alert management: A proactive defense against breaches. BigID. https://bigid.com/blog/alert-management/

6.Mayo Foundation for Medical Education and Research. (2024, April 17). Ai in healthcare: The future of patient care and health management. Mayo Clinic. https://mcpress.mayoclinic.org/healthy-aging/ai-in-healthcare-the-future-of-patient-care-and-health-management/#:~:text=What%20can%20AI%20technology%20in,costs%2C%20and%20benefitting%20population%20health

Buch, V. H., Ahmed, I., & Maruthappu, M. (2018b, March). Artificial Intelligence in medicine: Current trends and future possibilities. The British journal of general practice : the journal of the Royal College of General Practitioners. https://pmc.ncbi.nlm.nih.gov/articles/PMC5819974/#:~:text=FUTURE%20POSSIBILITIES%20IN%20GENERAL%20PRACTICE,also%20directly%20guide%20patient%20management

Overview Video

justasvysniauskas — 2025-03-14 20:13:51 UTC