AIMC Topic: Cancer Care Facilities

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The imitation game: large language models versus multidisciplinary tumor boards: benchmarking AI against 21 sarcoma centers from the ring trial.

Journal of cancer research and clinical oncology Sep 10, 2025
PURPOSE: The study aims to compare the treatment recommendations generated by four leading large language models (LLMs) with those from 21 sarcoma centers' multidisciplinary tumor boards (MTBs) of the sarcoma ring trial in managing complex soft tissu...
Humans Language Large Language Models Cancer Care Facilities Sarcoma Benchmarking
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Evaluation of a deep image-to-image network (DI2IN) auto-segmentation algorithm across a network of cancer centers.

Journal of cancer research and therapeutics Jan 22, 2024
PURPOSE/OBJECTIVE S: Due to manual OAR contouring challenges, various automatic contouring solutions have been introduced. Historically, common clinical auto-segmentation algorithms used were atlas-based, which required maintaining a library of self-...
Algorithms Prospective Studies Humans Cancer Care Facilities Image Processing, Computer-Assisted Radiotherapy Planning, Computer-Assisted Organs at Risk Neoplasms Deep Learning Tomography, X-Ray Computed
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Computer-aided detection and prognosis of colorectal cancer on whole slide images using dual resolution deep learning.

Journal of cancer research and clinical oncology Nov 4, 2022
PURPOSE: Rapid diagnosis and risk stratification can provide timely treatment for colorectal cancer (CRC) patients. Deep learning (DL) is not only used to identify tumor regions in histopathological images, but also applied to predict survival and ac...
Colorectal Neoplasms Deep Learning Prognosis Cancer Care Facilities Computers Humans
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A Cancer Paradox: Machine-Learning Backed Propensity-Score Analysis of Coronary Angiography Findings in Cardio-Oncology.

The Journal of invasive cardiology Jan 1, 2019
OBJECTIVES: Cancer has been proposed as a cardiovascular risk factor. We aimed to assess the cardiovascular risk profile and coronary angiography (CA) findings of cancer patients and compare them to those of patients without cancer.
Cancer Care Facilities Propensity Score Texas Neoplasms Multivariate Analysis Case-Control Studies Prevalence Humans Male Risk Assessment Female Aged, 80 and over Machine Learning Retrospective Studies Age Factors Aged Sex Factors Coronary Angiography Reference Values Logistic Models Academic Medical Centers Coronary Artery Disease
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Realizing the Promise of Cognitive Computing in Cancer Care: Ushering in a New Era.

JCO clinical cancer informatics Dec 1, 2018
Cancer Care Facilities Delivery of Health Care Deep Learning Artificial Intelligence Humans Neoplasms Cognition Algorithms
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