AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Neoplasms

Showing 361 to 370 of 1997 articles

Clear Filters

Bibliometric analysis of the application of deep learning in cancer from 2015 to 2023.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: Recently, the application of deep learning (DL) has made great progress in various fields, especially in cancer research. However, to date, the bibliometric analysis of the application of DL in cancer is scarce. Therefore, this study aime...

A deep-learning framework to predict cancer treatment response from histopathology images through imputed transcriptomics.

Nature cancer
Advances in artificial intelligence have paved the way for leveraging hematoxylin and eosin-stained tumor slides for precision oncology. We present ENLIGHT-DeepPT, an indirect two-step approach consisting of (1) DeepPT, a deep-learning framework that...

Application of Photoactive Compounds in Cancer Theranostics: Review on Recent Trends from Photoactive Chemistry to Artificial Intelligence.

Molecules (Basel, Switzerland)
According to the World Health Organization (WHO) and the International Agency for Research on Cancer (IARC), the number of cancer cases and deaths worldwide is predicted to nearly double by 2030, reaching 21.7 million cases and 13 million fatalities....

Tissue of origin detection for cancer tumor using low-depth cfDNA samples through combination of tumor-specific methylation atlas and genome-wide methylation density in graph convolutional neural networks.

Journal of translational medicine
BACKGROUND: Cell free DNA (cfDNA)-based assays hold great potential in detecting early cancer signals yet determining the tissue-of-origin (TOO) for cancer signals remains a challenging task. Here, we investigated the contribution of a methylation at...

Fairness in Predicting Cancer Mortality Across Racial Subgroups.

JAMA network open
IMPORTANCE: Machine learning has potential to transform cancer care by helping clinicians prioritize patients for serious illness conversations. However, models need to be evaluated for unequal performance across racial groups (ie, racial bias) so th...

Dual-stream multi-dependency graph neural network enables precise cancer survival analysis.

Medical image analysis
Histopathology image-based survival prediction aims to provide a precise assessment of cancer prognosis and can inform personalized treatment decision-making in order to improve patient outcomes. However, existing methods cannot automatically model t...

AI-Generated Content in Cancer Symptom Management: A Comparative Analysis Between ChatGPT and NCCN.

Journal of pain and symptom management
BACKGROUND: Artificial intelligence-driven tools, like ChatGPT, are prevalent sources for online health information. Limited research has explored the congruity between AI-generated content and professional treatment guidelines. This study seeks to c...

Artificial intelligence in radiotherapy: Current applications and future trends.

Diagnostic and interventional imaging
Radiation therapy has dramatically changed with the advent of computed tomography and intensity modulation. This added complexity to the workflow but allowed for more precise and reproducible treatment. As a result, these advances required the accura...

Potential application of artificial intelligence in cancer therapy.

Current opinion in oncology
PURPOSE OF REVIEW: This review underscores the critical role and challenges associated with the widespread adoption of artificial intelligence in cancer care to enhance disease management, streamline clinical processes, optimize data retrieval of hea...