Alan T. Bates | Nunez Lab for Computational Mental Health & Cancer Carehttps://example.com/authors/alan-t.-bates/Alan T. BatesWowchemy (https://wowchemy.com)en-usThu, 01 Jan 2026 00:00:00 +0000https://example.com/media/icon_huf7bff94e036df031df1d4c9565d99cb9_25138_512x512_fill_lanczos_center_3.pngAlan T. Bateshttps://example.com/authors/alan-t.-bates/Investigating fine-tuning versus zero-shot learning for general large language models when predicting cancer survival from initial oncology consultation documentshttps://example.com/publication/cancer_survival_llm_finetuning/Thu, 01 Jan 2026 00:00:00 +0000https://example.com/publication/cancer_survival_llm_finetuning/<p>This study investigates whether fine-tuning open-weight large language models (LLMs) improves cancer survival prediction from oncology consultation notes compared to zero-shot approaches. Using Meta&rsquo;s Llama models on 59,800 patient records from BC Cancer, fine-tuning consistently improved performance over zero-shot inference, but did not outperform smaller task-specific NLP models. The findings suggest both approaches merit continued investigation, with the best choice depending on clinical context and practical constraints such as hardware, privacy, and deployment feasibility.</p>Patients' Attitudes toward Artificial Intelligence (AI) in Cancer Care: A Scoping Review Protocolhttps://example.com/publication/ai_cancer_care_attitudes/Wed, 15 Jan 2025 00:00:00 +0000https://example.com/publication/ai_cancer_care_attitudes/<p>This scoping review protocol explores how patients with cancer perceive and accept artificial intelligence in their medical care, addressing an important gap in understanding patient perspectives on AI implementation in oncology.</p>Predicting Which Patients with Cancer Will See a Psychiatrist or Counsellor from Their Initial Oncology Consultation Document Using Natural Language Processinghttps://example.com/publication/cancer_psychiatric_nlp/Tue, 09 Apr 2024 00:00:00 +0000https://example.com/publication/cancer_psychiatric_nlp/<p>This groundbreaking study demonstrates that artificial intelligence can predict psychosocial needs of cancer patients by analyzing initial oncology consultation documents. Different linguistic patterns predict psychiatrist versus counselor referrals, providing clinically relevant insights for patient care.</p>Predicting the Survival of Patients With Cancer From Their Initial Oncology Consultation Document Using Natural Language Processinghttps://example.com/publication/cancer_survival_nlp/Mon, 27 Feb 2023 00:00:00 +0000https://example.com/publication/cancer_survival_nlp/<p>This study demonstrates that natural language processing applied to initial oncology consultation documents can effectively predict patient survival outcomes across multiple cancer types. The models perform comparably with or better than previous prediction models while using readily available clinical data.</p>Supportive Care and Health Care Service Utilization in Older Adults with a New Cancer Diagnosis: A Population Based Review in British Columbia, Canadahttps://example.com/publication/supportive_care_cancer_bc/Sun, 01 Jan 2023 00:00:00 +0000https://example.com/publication/supportive_care_cancer_bc/<p>This publication examines supportive care and health care service utilization patterns in older adults with new cancer diagnoses in British Columbia.</p>