Longitudinal Insights for People Living with Type 1 Diabetes; Ethical Dilemma of Euthanasia
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Notice bibliographique
Résumé
Technical Project Report Type 1 diabetes (T1D) is a chronic autoimmune condition where the immune system attacks and destroys insulin-producing beta cells in the pancreas. Demanding strict management of blood glucose and insulin levels, patients use devices such as continuous glucose monitors (CGMs), insulin pumps, and other related technologies. Despite the advances in these tools, the complexity of diabetes makes the fragmented data hard to interpret for an average clinician or patient, especially over extended time periods. My capstone project enhances the Tidepool platform, a non-profit and open-source diabetes data management tool, by integrating new features that transform raw data into actionable insights. In order to achieve a particular goal, two specific aims were set. The first aim is to develop an algorithm that identifies critical fluctuations in glucose and insulin levels on daily and weekly scales. This algorithm uses patients’ CGM data to detect and visualize daily and weekly variations in diabetes device data. While highlighting critical times when patients should be more vigilant, the algorithm also generates targeted response prompts based on the identified times and guides the patient on how to act accordingly. The second aim is developing a 5-minute summary feature that would translate a patient's monthly data into a prioritized, personalized visual. This includes analysis of behavioral factors affecting glycemic control and specific recommendations for improvement. The goal is to equip patients with a better understanding of how their habits influence their diabetes management and help clinician make informed, individualized care decisions for their patients, especially in areas where access to Certified Diabetes Care and Education Specialists (CDCES) isn’t attainable. By leveraging data integration, algorithms, and user-friendly visualization, these enhancements to Tidepool will undoubtfully encourage better disease management, improve treatment, and lead to better clinical outcomes. There is hope of significant advancement in accessibility and effectiveness of diabetes care for everyone with the work being done in this project. STS Research Project Euthanasia, the deliberate act of ending a person’s life to relieve suffering, remains one of the most ethically and legally controversial practices in modern medicine. This paper explores the complex history, evolving definitions, and moral debates surrounding euthanasia, tracing its roots from Ancient Greek and Roman acceptance to its condemnation under early Christian doctrine. The discussion transitions into the modern understanding of euthanasia, emphasizing Samuel Williams' 19th-century proposal to legalize it and its lasting impact on the discourse. A focal point of the paper is Jack Kevorkian, a pathologist whose publicized involvement in over 100 assisted suicides, particularly the videotaped death of ALS patient Thomas Youk, ignited national debate and legal repercussions, ultimately influencing public and legal perspectives on end-of-life autonomy. The paper also examines Canada's Medical Assistance in Dying (MAID) program, highlighting growing concerns that financial hardship and lack of adequate support systems may coerce vulnerable individuals into choosing death. Ethical dilemmas, like the subjective nature of pain, potential for abuse, and the role of social support in end-of-life decisions, are carefully analyzed to offer clear understanding of both sides of euthanasia. Since I purely used a research approach, I focused on making sure the sources used offer an accurate narrative; this meant using scholarly articles, historical texts, and legal documents. Rather than advocating a specific stance myself, I encourage readers to reflect on the multifaceted nature of euthanasia and form their own ethical conclusions. How are these related? Although both topics don’t seem directly related, they share values that I find critically important. With their distinct focus and methodology, the two projects are still connected as they address systemic inequities, advocate for human dignity, and explore how medical technologies and data influence can seriously influence healthcare decisions. My technical project seeks to empower individuals with Type 1 diabetes by translating complex CGM data into meaningful insights that can guide patients and clinicians in managing this condition. By enhancing the Tidepool platform, the project presents a clear prioritization of patient autonomy and patient agency, allowing these individuals to be able to make informed decisions, even when they don’t have specialized support readily available. Similarly, my STS project on euthanasia investigates how and why individuals exercise autonomy when in comes to life and death, with an emphasis on how medical systems and societal structures influence choices. Together, these projects highlight ethical and practical intersections of technology and healthcare. Whether through tools to support chronic disease management or critical analysis of euthanasia laws and ethics, I show how the societal and systematic part of medicine can significantly enhance or constrain quality of life. With optimism, I believe these projects advocate for a more empathetic and user-centered approach to healthcare that respects individual needs while addressing broader systemic challenges.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle