Date of Award
2024
Degree Name
Healthcare Administration
College
College of Business
Type of Degree
M.S.
Document Type
Research Paper
First Advisor
Alberto Coustasse, Dr.PH. MD, MBA, MPH
Abstract
Introduction: The introduction of Artificial Intelligence (AI) in the healthcare setting has promoted benefits in cancer treatment for many forms of cancer, especially breast cancer. This additional measure has brought a second set of eyes to medical images involving cancer diagnosis and treatment. Being regulated by the Food and Drug Administration, facilities utilize these tools increasingly. There is concern as to if the accuracy truly benefits the patient and if radiologists are solely relying on these additional methods.
Purpose of the Study: The purpose of this study was to analyze the use of AI in early breast cancer detection for patients in the U.S. and how it impacted patient mortality rates, the cost of treatment, and the duration of treatment.
Methodology: This study was a literature review. Three databases were used to collect a total of 62 sources. These sources were analyzed thoroughly and reduced to 30 sources that were fully utilized in the research writing. Of the sources utilized, 20 were used within the results section.
Results: The research showed quality measures such as breast cancer detection, differentiate between benign and malignant, survival rates, and cost effectiveness. An overall increase in sensitivity and accuracy were proven with the additional use of AI than readings without the utilization of this tool. Radiologist that used AI in comparison than using two radiologists, also increased the specificity of the reading report. False negative rates were decreased with the assistance of AI-assisted surgery.
Discussion/Conclusion: Cost effectiveness and overall improvement on the diagnostic imaging reports were increased with the utilization of AI assistance. Improving reading reports, along with the speed of results can decrease mortality rate. The findings were inconclusive as to whether there was a decrease in total treatment duration, due to an earlier detection rate. Farther patient data collection would need to have been collected to obtain this information.
Subject(s)
Health services administration.
Health facilities -- Business management.
Artificial intelligence.
Breast -- Cancer -- Treatment.
Breast -- Cancer -- Diagnosis.
Oncology.
Radiology.
Recommended Citation
McDaniel, Marlee and Toppins, Mikayla, "AI and its use in cancer treatment" (2024). Theses, Dissertations and Capstones. 1901.
https://mds.marshall.edu/etd/1901
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