{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T04:55:05Z","timestamp":1788238505304,"version":"build-2803163510"},"reference-count":115,"publisher":"MJH Life Sciences","issue":"10","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,11,24]]},"abstract":"<jats:p>Artificial intelligence (AI) is transforming health care by enhancing diagnostics, treatment planning, and patient monitoring. In palliative oncology, particularly for hematologic malignancies, AI has shown promise in improving symptom management, prognostication, and personalized care. AI-driven models utilizing electronic health records, wearable devices, and predictive analytics aid in the early detection of symptoms, optimization of pain management, and streamlining of clinical decision-making. Machine learning algorithms have also enhanced risk stratification in leukemia, lymphoma, and multiple myeloma by integrating genomic data, imaging, and treatment responses to refine prognostic models. Additionally, AI-powered tools support cancer survivorship by monitoring late-treatment effects and aiding end-of-life care through predictive analytics for timely palliative interventions. Despite these advancements, challenges remain, including data bias, ethical concerns, and the need for prospective validation in clinical settings. Addressing these limitations will be crucial for fully integrating AI into palliative oncology and hematologic malignancy care.<\/jats:p>","DOI":"10.46883\/2025.25921057","type":"journal-article","created":{"date-parts":[[2025,12,10]],"date-time":"2025-12-10T18:20:49Z","timestamp":1765390849000},"page":"468","source":"Crossref","is-referenced-by-count":4,"title":["The Role of Artificial Intelligence in Palliative Oncology: Zeroing in on Hematologic Malignancies"],"prefix":"10.46883","volume":"39","author":[{"given":"Ram Prakash","family":"Thirugnanasambandam","sequence":"first","affiliation":[{"name":"University of Nebraska Medical Center"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ariana","family":"Bauer","sequence":"additional","affiliation":[{"name":"University of Nebraska Medical Center"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christopher","family":"D\u2019Angelo","sequence":"additional","affiliation":[{"name":"University of Nebraska Medical Center"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"25947","published-online":{"date-parts":[[2025,12,3]]},"reference":[{"key":"ref0","doi-asserted-by":"crossref","unstructured":"1.Bekbolatova M, Mayer J, Ong CW, Toma M. 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