Publications by authors named "Ken Cheligeer"
Article Synopsis
- The study aimed to assess how well Large Language Models (LLMs) can understand complex medical documents, specifically focusing on identifying pathologic complete response (pCR) in breast cancer pathology reports.
- Researchers used two methods to analyze data from pathology reports: extracting features with transformer-based models and fine-tuning GPT-2 to enhance pCR detection accuracy.
- Results showed high accuracy (95.3% sensitivity and 90.9% positive predictive value) in identifying pCR, demonstrating that LLMs can outperform traditional machine learning techniques in clinical pathology analysis.
Alberta has rich clinical and health services data held under the custodianship of Alberta Health and Alberta Health Services (AHS), which is not only used for clinical and administrative purposes but also disease surveillance and epidemiological research. Alberta is the largest province in Canada with a single payer centralised health system, AHS, and a consolidated data and analytics team supporting researchers across the province. This paper describes Alberta's data custodians, data governance mechanisms, and streamlined processes followed for research data access.
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