Can ChatGPT and DeepSeek help cancer patients: A comparative study of artificial intelligence models in clinical decision support
Year: 2025
Type: article
Abstract: BACKGROUND Cancer care faces challenges due to tumor heterogeneity and rapidly evolving therapies, necessitating artificial intelligence (AI)-driven clinical decision support. While general-purpose models like ChatGPT offer adaptability, domain-specific systems (e.g. , DeepSeek) may better align with clinical guidelines. However, their comparative efficacy in oncology remains underexplored. This study hypothesizes that domain-specific AI will outperform general-purpose models in technical accuracy, while the latter will excel in patient-centered communication. AIMS To compare ChatGPT and DeepSeek in oncology decision support for diagnosis, treatment, and patient communication. METHODS A retrospective analysis was conducted using 1200 anonymized oncology cases (2018–2023) from The Cancer Genome Atlas and institutional databases, covering six cancer types. Each case included histopathology, imaging, genomic profiles, and treatment histories. Both models generated diagnostic interpretations, staging assessments, and therapy recommendations. Performance was evaluated against NCCN/ESMO guidelines and expert oncologist panels using F1-scores, Cohen's κ, Likert-scale ratings, and readability metrics. Statistical significance was assessed via analysis of variance and post-hoc Tukey tests. RESULTS DeepSeek demonstrated superior performance in diagnostic accuracy (F1-score: 89.2% vs ChatGPT's 76.5%, P < 0.001) and treatment alignment with guidelines (κ = 0.82 vs 0.67, P = 0.003). ChatGPT exhibited strengths in patient communication, generating layman-friendly explanations (readability score: 8.2/10 vs DeepSeek's 6.5/10, P = 0.012). Both models showed limitations in rare cancer subtypes (e.g. , cholangiocarcinoma), with accuracy dropping below 60%. Clinicians rated DeepSeek's outputs as more actionable (4.3/5 vs 3.7/5, P = 0.021) but highlighted ChatGPT's utility in palliative care discussions. CONCLUSION Domain-specific AI (DeepSeek) excels in technical precision, while general-purpose models (ChatGPT) enhance patient engagement. A hybrid system integrating both approaches may optimize oncology workflows, contingent on expanded training for rare cancers and real-time guideline updates.
Language: English
Subfield: Health Informatics
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
Awards: G1083213090, G111615301, G1387502171, G139585312, G1494577930, G1574102252, G1609525565, G1901027039, G2049268772, G2659503640, G2664783788, G272783259, G2745790217, G2826276765, G2851467072, G2857508635, G2894286751, G2913522532, G3325473034, G3331582980, G3746653997, G3782257663, G384457986, G3939518057, G4051143537, The Human Genome Sequencing Center, Harvard Genome Characterization Center, G5005221876, Cancer transcriptome characterization using massively parallel DNA sequencing, G5181012032, G5230311920, G5711250986, G648251598, G6736661663, G7097003521, G7208951124, G7438649735, G8198881356, G8879124269, G9000018409, G9000019010, G9000022338, G9000022781, G9000033506, G9000034222, G9000048103, G9000052705, G9000062434, G9000079746, G9000086836, G9000176922, G9000179146, G9000186802, G9000193931, G9000244592, G9000305565
OpenAlex ID: W4411048626