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- Creators: College of Health Solutions
Specifically, this thesis focuses on the formulation of a Markov Chain model that is complex and robust. This Markov Chain model emulates the evolution of MCI patients based upon doctor visits and the sequential administration of biomarker tests. Data provided to create this Markov Chain model were collected by the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. The data lacked detailed information of the sequential administration of the biomarker tests and therefore, different analytical approaches were tried and conducted in order to calibrate the model. The resulting Markov Chain model provided the capability to conduct experiments regarding different parameters of the Markov Chain and yielded different results of patients that contracted AD and those that did not, leading to important insights into effect of thresholds and sequence on patient prediction capability as well as health costs reduction.
The data in this thesis was provided from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu). ADNI investigators did not contribute to any analysis or writing of this thesis. A list of the ADNI investigators can be found at: http://adni.loni.usc.edu/about/governance/principal-investigators/ .
Medical recovery time continues to be a drawback for many medical diagnoses and procedures. Prolonged recovery affects all aspects of the population, and targets different avenues of everyday life. Avenues such as providing, attending a job, personal objectives in different ways and even their own well-being. To combat this one area of research that has gained tremendous awareness in recent years is that of platelet-rich fibrin (PRF), which has been utilized across a wide variety of medical fields for the regeneration of soft tissues. PRF, or platelet-rich fibrin, is the next generation treatment of platelet concentrate. PRF is a fibrin matrix composed of platelet cytokines, growth factors and cells used to help wound healing and tissue regeneration. The objective of this thesis is to investigate the potential recovery time difference with PRF incorporation for common medical procedures. The experimental group included three individuals who had PRF treatment at any point during any sort of medical operation. The control group included individuals who did not have PRF treatment at any point and also those who had no prior knowledge of this method of treatment. Results were mixed because of the variative behind the medical procedures. Through observation, PRF treatment improved tolerance of pain, well-being of patients and quality of recovery with three different domains of inquiry per patient testimony. This case-analysis of 6 patients is a preliminary study and therefore inconclusive. PRF is a promising approach and this study suggests that it could potentially be a new medical approach to treatment.
This research paper focuses on how the idea of suffering has evolved over time in the United States healthcare system. Different aspects like long vs short-term illnesses, bias, and more were inspected to determine how they play a part in increased or decreased patient suffering. The final determination of how suffering in the system has evolved and what to do with this information is also discussed.
This thesis explores the ethical implications of using facial recognition artificial intelligence (AI) technologies in medicine, with a focus on both the opportunities and challenges presented by the use of this technology in the diagnosis and treatment of rare genetic disorders. We highlight the positive outcomes of using AI in medicine, such as accuracy and efficiency in diagnosing rare genetic disorders, while also examining the ethical concerns including bias, misdiagnosis, the issues it may cause within patient-clinician relationships, misuses outside of medicine, and privacy. This paper draws on the opinions of medical providers and other professionals outside of medicine, which finds that while many are excited about the potential of AI to improve medicine, concerns remain about the ethical implications of these technologies. We discuss current legislation controlling the use of AI in healthcare and its ambiguity. Overall, this thesis highlights the need for further research and public discourse to address the ethical implications of using facial recognition and AI technologies in medicine, while also providing recommendations for its future use in medicine.
encounter in the medical world. The concept for this paper originates from the idea of narrative
medicine as a way to foster relationships between physicians and patients through the sharing of
stories, or narratives, between the two parties. In efforts to help teach this skill, universities and
medical schools have begun to offer courses in the medical humanities. The goal of these courses
is to teach students how to develop the skills they need to empathize and learn from their
patients’ experiences. Paired with the traditional rigor of a science-based curriculum, the medical
humanities have become part of medical schools’ efforts to “train the whole physician.”
Medical poetry is an example of the types of humanities courses that can benefit students
interested in medicine. The history of medical poetry spans across decades of literary history.
Beginning with the early references of medicine from the ancient world to the contemporary
work of the present, poets of different backgrounds and histories are discussed. Research to
support the efficacy of medical poetry include studies done on how medical poetry has impacted
students, readers, and patients. Finally, the author’s experiences as both a pre-professional
student and patient are shared to further explore the benefits that reading, and writing can bring.