AIMC Topic: Neoplasms

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In-Hospital Cancer Mortality Prediction by Multimodal Learning of Non-English Clinical Texts.

Studies in health technology and informatics
Predicting important outcomes in patients with complex medical conditions using multimodal electronic medical records remains challenge. We trained a machine learning model to predict the inpatient prognosis of cancer patients using EMR data with Jap...

The evolution of cancer genomic medicine in Japan and the role of the National Cancer Center Japan.

Cancer biology & medicine
The journey to implement cancer genomic medicine (CGM) in oncology practice began in the 1980s, which is considered the dawn of genetic and genomic cancer research. At the time, a variety of activating oncogenic alterations and their functional signi...

Natural Language Processing Methods to Empirically Explore Social Contexts and Needs in Cancer Patient Notes.

JCO clinical cancer informatics
PURPOSE: There is an unmet need to empirically explore and understand drivers of cancer disparities, particularly social determinants of health. We explored natural language processing methods to automatically and empirically extract clinical documen...

Novel Generative Recurrent Neural Network Framework to Produce Accurate, Applicable, and Deidentified Synthetic Medical Data for Patients With Metastatic Cancer.

JCO clinical cancer informatics
PURPOSE: Sensitive patient data cannot be easily shared/analyzed, severely limiting the innovative progress of research, specifically for marginalized/under-represented populations. Existing methods of deidentification are subject to data breaches. T...

Use of artificial intelligence for cancer clinical trial enrollment: a systematic review and meta-analysis.

Journal of the National Cancer Institute
BACKGROUND: The aim of this study is to provide a comprehensive understanding of the current landscape of artificial intelligence (AI) for cancer clinical trial enrollment and its predictive accuracy in identifying eligible patients for inclusion in ...

Drug repurposing for viral cancers: A paradigm of machine learning, deep learning, and virtual screening-based approaches.

Journal of medical virology
Cancer management is major concern of health organizations and viral cancers account for approximately 15.4% of all known human cancers. Due to large number of patients, efficient treatments for viral cancers are needed. De novo drug discovery is tim...

Using ChatGPT to evaluate cancer myths and misconceptions: artificial intelligence and cancer information.

JNCI cancer spectrum
Data about the quality of cancer information that chatbots and other artificial intelligence systems provide are limited. Here, we evaluate the accuracy of cancer information on ChatGPT compared with the National Cancer Institute's (NCI's) answers by...

Artificial intelligence chatbots will revolutionize how cancer patients access information: ChatGPT represents a paradigm-shift.

JNCI cancer spectrum
On November 30, 2022, OpenAI enabled public access to ChatGPT, a next-generation artificial intelligence with a highly sophisticated ability to write, solve coding issues, and answer questions. This communication draws attention to the prospect that ...

Single-cell gene regulatory network prediction by explainable AI.

Nucleic acids research
The molecular heterogeneity of cancer cells contributes to the often partial response to targeted therapies and relapse of disease due to the escape of resistant cell populations. While single-cell sequencing has started to improve our understanding ...