Correlation between Cancer Research Trends and the Importance of Cancers based on Mortality and Diagnosis Rates: An Analysis of Altmetric Data
Notice bibliographique
Résumé
Aside from the infrequent news pertaining to medical breakthroughs or dangers to the public, medical research, especially in the field of cancer, is rarely discussed in depth. The public does not know the process in which specific fields of medical research receive funding, or how this funding is used to limit issues such as cancer. This study aims to provide clarity on cancer research trends. The amount of research papers pertaining to different types of cancers is compared against mortality and diagnosis rates to determine the amount of research attention given to a type of cancer, in relation to its effects on the general population. Computational tools, such as Python, R, and Microsoft Excel, were used to analyze a dataset of research papers. Python was used to parse through JSON files and extract the abstract and Altmetric score of cancer research papers. R was used to count the appearance of each type of cancer in the abstracts, and create histograms describing Altmetric scores and file frequency. Microsoft Excel was used to find correlations between Altmetrics’ data and Canadian Cancer Society data, linking the amount of research to the impacts of cancer based on deaths and new cases. The analysis from these tools revealed that breast cancer was the most researched cancer by a large margin, with nearly 1,700 papers, which is approximately four times the amount of the next leading type of cancer – prostate cancer. Although there were many research papers on the field of cancer, the Altmetric scores revealed that most of these papers did not gain significant online and media attention. Comparing these results to Canadian Cancer Society data showed that breast cancer was receiving more research attention than the mortality and diagnosis rates suggest it should. There were four times more breast cancer research papers than the secondmost researched cancer, prostate cancer. This was despite the fact that breast cancer was fourth in mortality and third in new cases among all types of cancer. Inversely, lung cancer was underrepresented, with only 401 research papers, despite being the deadliest cancer in Canada.
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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 | 0,005 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| 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 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 ».