Discuss The effects of the advancing role of AI in biomedical engineering
Which application of AI is the most effective in alleviating errors and improving the efficiency of the medical industry in the United States?
SUMMARY OF RESEARCH:
A recent study revealed that the 3rd-leading cause of death in the U.S. is a medical error, and that medical malpractice may account for as many as 251,000 deaths annually. AI technologies can drastically help physicians provide healthcare more effectively using machine learning and pattern recognition algorithms, and while artificial intelligence is not completely error-free, it is relatively more accurate than humans. My research’s goal is to determine which application of AI – Intelligent Robots, Image Recognition Technology, Diagnosis/Treatment, Surgical Assistance, Drug Discovery – will prove to be the most effective in preventing medical errors that many healthcare workers execute. To do this I will use content analysis, and the criteria I will use to compare each application of AI are: Functionality/Purpose in Health Systems, Feasibility/Cost of Implementation, Average Number of Errors Made By Physicians(Per Year), Accuracy of the AI Compared to Physician.
I have uploaded a rubric and an example paper of what mine should look like. I have uploaded my paper as well as my content analysis table (shown in Appendix A) and my sources (shown in References). The whole paper that I’ve attached shows a rough idea of what the final product should look like. I just need to replace that information with real information from the sources I provided. I also need parenthetical citations for whichever sources you use from my references page.
This may seem confusing, so please message me if you need any further clarification, THANK YOU!!
Improved diagnosis: AI has the ability to analyze large volumes of data, including medical images and patient histories, and identify patterns that may be difficult for human doctors to detect. This could lead to earlier and more accurate diagnoses, which could improve patient outcomes and save lives.
Personalized treatment: AI can also help to tailor treatment plans to individual patients based on their specific characteristics
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Drug discovery: AI can analyze large volumes of data from clinical trials and other sources to identify new drug targets and potential treatments for a variety of diseases. This could speed up the drug discovery process and lead to new treatments for previously untreatable conditions.
Improved surgical outcomes: AI can assist surgeons during complex procedures by providing real-time feedback and guidance. This could lead to fewer complications and better surgical outcomes for patients.
Remote monitoring: AI can be used to monitor patients remotely, which could help to reduce the burden on healthcare systems and improve access to care for patients in remote or underserved areas.
Ethical considerations: With the increasing role of AI in healthcare, there are ethical considerations to be addressed, such as ensuring patient privacy and addressing concerns around algorithmic bias.
Overall, the advancing role of AI in biomedical engineering has the potential to improve patient outcomes, accelerate the drug discovery process, and improve access to care for patients. However, it is important to carefully consider the ethical implications of these advances and ensure that they are used in a responsible and equitable manner.