An Innovative New Graduate Program That Promotes Direct Entry to Physiology Related Careers: The Master of Health Science in Medical Physiology
Notice bibliographique
Résumé
There are many career possibilities that physiology students can pursue, as it is a discipline that not only underlies further health-science specializations, but also related areas in biotechnology, pharmaceuticals, and health related data science. Students are often not aware of these careers, or lack skills beyond scientific training, including knowledge of commercialization or data analytics that would allow them to directly enter these areas. To this end, the Department of Physiology at the University of Toronto developed a new graduate program to train students to bridge the gap of taking existing physiological knowledge concerning human health and put it into practice into emerging areas related to health. The resulting Master of Health Science in Medical Physiology is a one year, course-based, professional degree, and represents an innovative approach to graduate education in a traditional Physiology department. The program combines courses in advanced physiology, with a mentored literature review report, new courses in commercialization, big data analysis, and clinical applications, as well as embedded professional development and career exploration. Finally, a practicum placement in the last term allows students to explore how human physiology is integrated and applied in different work environments such as industry, clinical research, or consulting. Results of anonymous student surveys (University of Toronto REB#38711) indicated that students felt more aware and prepared for careers in areas of interest to them. Indeed, testimonials from practicum supervisors reveal that our graduates bring a unique skillset that is highly valued in both academic and non-academic organizations. Early graduate outcome tracking data since our first cohort in 2021 demonstrates that the novel approach of the program prepares students to enter directly into physiology careers. While approximately one third of graduates pursue further health studies such as medicine, most of our graduates are directly employed in different sectors such as biotechnology, consulting, medical communications, data analytics, artificial intelligence, and more – aligning with the program’s goals. In this work, we will describe the development, implementation, and impact of the new MHSc Medical Physiology graduate program. This abstract was presented at the American Physiology Summit 2025 and is only available in HTML format. There is no downloadable file or PDF version. The Physiology editorial board was not involved in the peer review process.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
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 | 0,003 | 0,011 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,003 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».