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By increasing patient care, customizing therapies, and improving diagnostic precision, artificial intelligence is transforming the healthcare industry. I picked this field because AI has the potential to change the way we diagnose, treat, and manage illnesses, and healthcare is an important part of society. I think AI is helping doctors make better decisions, lowering human error, and eventually saving lives. I'm also interested in this area since I am majoring in psychology, so these themes are intriguing to me and will inform me about the role AI plays in healthcare.

One of the most exciting aspects of AI in healthcare is its ability to process vast amounts of medical data quickly. Medical picture analysis by AI-driven algorithms can identify diseases like cancer early on and anticipate patient decline before it occurs. Faster patient outcomes, treatment plans, and diagnosis are the results of these developments.

I'll look at three important uses of AI in healthcare:

1. AI in Diagnostic Imaging: AI-driven technologies help radiologists more accurately diagnose conditions including cancer and neurological problems.

2. AI in Personalized Medicine: Machine learning creates more effective medicines by customizing them for each patient based on their genetics, lifestyle, and medical information.

3. AI in Patient Monitoring: Wearables with AI capabilities continuously monitor vital indicators, enabling early health issue identification and treatment.

The application of AI in healthcare is innovative, but it also brings up moral questions about algorithmic bias and data privacy. Investigating this subject will help me to understand its advantages and difficulties in influencing medical advancement.

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AI has transformed diagnostic imaging by helping radiologists more accurately and efficiently identify diseases including cancer, fractures, and neurological disorders. AI systems can examine medical images, such as X-rays, MRIs, and CT scans, using machine learning and computer vision to find errors that the human eye could miss. For example, the FDA has approved about 400 AI algorithms for the radiology industry due to AI's capacity to handle enormous volumes of both organized and unstructured data (American Hospital Association, 2023). However problems still exist, such as algorithmic biases and the requirement for high-quality datasets to guarantee accuracy. AI is still improving medical diagnostics despite these obstacles (Forbes Technology Council, 2025). I find this exciting as it is very beneficial as it gives early diagnosis and quicker methods for treatment are made possible by this ability.

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Using artificial intelligence in radiology clinical practice

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Healthcare - AI in Personalized Medicine

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Healthcare - AI in Personalized Medicine

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By customizing medicines for each patient according to their distinct genetic structure, lifestyle, and environmental circumstances, artificial intelligence is bringing about a new era of customized medicine. AI systems, for instance, can analyze genomic data to find certain mutations, allowing for customized treatments for diseases like cancer (Springer, 2025). This method reduces side effects while increasing treatment efficacy. Nonetheless, issues like the requirement for standardized data formats and data privacy concerns still exist. However, there is great potential for bettering patient outcomes through the use of AI in customized medicine (HealthOn, 2025). I find this revolutionary that AI can help individuals with terrible illnesses but dictating lifestyle changes and treatments that can truly benefit them over time. As a person who sees chronic illnesses in my family, I have hope that this help people.

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VJHemOnc – Video Journal of Hematology & HemOnc

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The role of artificial intelligence for precision medicine in multiple myeloma

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Wearable technology driven by artificial intelligence is improving patient monitoring by continuously and instantly tracking vital signs including blood pressure, oxygen saturation, and heart rate. These gadgets, which use deep learning and Internet of Medical Things (IoMT) technology, can identify early indicators of health decline and enable timely medical interventions. For example, combining deep learning models with IoMT improves predictive analytics and diagnostic precision, resulting in more individualized care (Devdiscourse, 2025). Nonetheless, there are difficulties in managing the enormous volumes of data produced and guaranteeing data security. AI-driven patient monitoring systems have the potential to greatly enhance healthcare delivery despite these problems (Medicai, 2025). With this AI technology, I believe that several mishaps can be prevented therefore bettering the healthcare system overall.

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Remote Patient Monitoring Unveiled: Transforming Healthcare with Cameras and AI

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Future Trends and Ethical Considerations

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Future Trends and Ethical Considerations

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With developments in virtual health assistants, robotically assisted surgery, and predictive analytics, artificial intelligence is set to change the healthcare industry completely. AI can evaluate patient data and predict possible health hazards thanks to predictive analytics, which enables early interventions and lowers hospital readmission rates (Mayo Clinic Press, 2024). In difficult procedures, robotic-assisted surgery improves precision, reduces human error, and speeds up recovery (Forbes Business Council, 2025). In the meantime, AI-driven virtual health assistants increase access to healthcare services by offering round-the-clock patient support (CDC, 2024).

However, when AI is incorporated into healthcare more and more, ethical issues come up. Bias in AI algorithms is a significant worry since it may result in unequal diagnoses and treatments for marginalized groups if AI is trained on biased datasets (CDC, 2024). Another concern is patient data privacy because AI systems need a lot of private health data, which raises the possibility of data breaches (AMA, 2024). Furthermore, relying too much on AI could lessen human oversight in crucial medical choices, which would raise questions about responsibility in the event of mistakes (Cedars-Sinai, 2025).

Even though AI has a lot of promise, its proper application in healthcare depends on resolving these ethical issues. For AI to help all patients fairly and securely, it will be crucial to strike a balance between innovation and ethical responsibility (Forbes Business Council, 2025). In conclusion, I believe that with proper precautionary measures, AI is and will benefit humanity as time progresses.

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Healthcare is being revolutionized by AI, but the effects on society are multifaceted, presenting both opportunities and difficulties. Increased accessibility to healthcare is one significant advantage. By enabling remote medical consultations for underprivileged populations, AI-powered virtual assistants and telemedicine systems help to close the gap in healthcare (Mayo Clinic Press, 2024). Additionally, early disease diagnosis is improved by AI-driven predictive analytics, which lowers healthcare costs and improves patient outcomes (Forbes Business Council, 2025).

But AI also raises issues with employment. Automation may lead to the replacement or restructuring of administrative and diagnostic jobs, which would impact the job security of healthcare workers (CDC, 2024). Although artificial intelligence (AI) has the potential to improve workflows, excessive dependence on technology could reduce the human component of patient care (Cedars-Sinai, 2025).

Another important concern is privacy. Large volumes of patient data are needed for AI systems, which raises the possibility of data breaches and misuse (AMA, 2024). Sustaining patient trust requires robust data protection mechanisms. Furthermore, if datasets are not diverse, bias in AI algorithms may result in inequities in care, especially for underrepresented communities (CDC, 2024).

Despite these obstacles, I believe AI has a generally good impact on healthcare—as long as ethical issues are given first priority. In order to provide fair and efficient patient care for everyone, the future of AI in healthcare must strike a balance between technical advancement and human supervision (Forbes Business Council, 2025).

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My grasp of AI's effects on patient monitoring, customized medicine, and diagnostics has grown as a result of my research in the field. Finding reliable sources was difficult for me, but I overcame this by consulting industrial and scholarly studies, such as those from the AMA and CDC. Additionally, I struggled with adding videos from YouTube to my Padlet post and was not able to complete the 4-5 minute overview video due to Padlet limiting me to 2 minutes therefore I sent the video separately on Brightspace to fulfill the requirement. It was also challenging to summarize sophisticated AI technologies; nonetheless, it was helpful to divide them into applications, advantages, and difficulties. My perspective on the function of AI has been altered by this research; while it presents amazing improvements, it also brings up ethical issues like bias and data privacy. As we advance, I think ethical AI use is crucial to guaranteeing fair and efficient healthcare improvements.

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American Medical Association. (2024). AI in healthcare: Trends and ethical considerations. Retrieved from www.ama-assn.org
Rationale: This source provides insights into the latest AI advancements in healthcare and ethical concerns.

Centers for Disease Control and Prevention. (2024). AI in public health and patient monitoring. Retrieved from www.cdc.gov
Rationale: This report explains how AI is used for disease detection, remote monitoring, and public health management.

Forbes Business Council. (2025). How AI is reshaping personalized medicine. Forbes. www.forbes.com
Rationale: This article explores AI’s role in tailoring treatments based on individual patient data.

Mayo Clinic Press. (2024). AI-driven diagnostic imaging and its impact on accuracy. www.mayoclinic.org
Rationale: This source details how AI is improving diagnostic imaging in radiology.

Cedars-Sinai. (2025). Ethical challenges of AI in healthcare. www.cedars-sinai.org
Rationale: This report highlights ethical concerns, including AI bias and patient data security.

IBM Watson Health. (2024). AI and machine learning in medical diagnostics. www.ibm.com
Rationale: This source discusses IBM Watson’s role in AI-driven diagnostics and its benefits in improving accuracy.

Tempus. (2025). Advancing precision medicine with AI and genomic data. www.tempus.com
Rationale: This article explains how AI is used in genomic analysis to create personalized treatment plans.