AIMC Topic: Neoplasms

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An improved cancer diagnosis algorithm for protein mass spectrometry based on PCA and a one-dimensional neural network combining ResNet and SENet.

The Analyst
Cancer is one of the most serious health problems worldwide. Because cancer has no specific symptoms in its early stages, it is often not diagnosed until it is in advanced stages, reducing the likelihood of successful treatment. Therefore, early diag...

Application of magnetic resonance imaging and artificial intelligence algorithms in cancer screening.

SLAS technology
In this society with a high incidence of cancer, cancer screening has become an important method to reduce the incidence and mortality of cancer. Traditional cancer screening methods such as CT have certain limitations and are difficult to adapt to l...

Machine learning models for risk prediction of cancer-associated thrombosis: a systematic review and meta-analysis.

Journal of thrombosis and haemostasis : JTH
BACKGROUND: Although the number of models for predicting the risk of cancer-associated thrombosis has been rising, there is still a lack of comprehensive assessment for machine learning prediction models.

Non-invasive multiple cancer screening using trained detection canines and artificial intelligence: a prospective double-blind study.

Scientific reports
The specificity and sensitivity of a simple non-invasive multi-cancer screening method in detecting breast, lung, prostate, and colorectal cancer in breath samples were evaluated in a double-blind study. Breath samples of 1386 participants (59.7% mal...

Impact of Image Content on Medical Crowdfunding Success: A Machine Learning Approach.

Journal of medical Internet research
BACKGROUND: As crowdfunding sites proliferate, visual content often serves as the initial bridge connecting a project to its potential backers, underscoring the importance of image selection in effectively engaging an audience.

Artificial intelligence neural network and fuzzy modelling of unsteady Sisko trihybrid nanofluids for cancer therapy with entropy insights.

Scientific reports
The main objective of the current endeavor is to monitor hypothetical processes utilizing a Sisko tri-hybrid fluid over a rotating disk with entropy generation suspended in Darcy-Forchheimer porous medium. Electro Magneto Hydro Dynamics (EMHD), non-l...

From Images to Genes: Radiogenomics Based on Artificial Intelligence to Achieve Non-Invasive Precision Medicine in Cancer Patients.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
With the increasing demand for precision medicine in cancer patients, radiogenomics emerges as a promising frontier. Radiogenomics is originally defined as a methodology for associating gene expression information from high-throughput technologies wi...

Drug Sensitivity Prediction Based on Multi-stage Multi-modal Drug Representation Learning.

Interdisciplinary sciences, computational life sciences
Accurate prediction of anticancer drug responses is essential for developing personalized treatment plans in order to improve cancer patient survival rates and reduce healthcare costs. To this end, we propose a drug sensitivity prediction model based...

Shareable artificial intelligence to extract cancer outcomes from electronic health records for precision oncology research.

Nature communications
Databases that link molecular data to clinical outcomes can inform precision cancer research into novel prognostic and predictive biomarkers. However, outside of clinical trials, cancer outcomes are typically recorded only in text form within electro...

A bibliometrics analysis based on the application of artificial intelligence in the field of radiotherapy from 2003 to 2023.

Radiation oncology (London, England)
BACKGROUND: Recent research has demonstrated that the use of artificial intelligence (AI) in radiotherapy (RT) has significantly streamlined the process for physicians to treat patients with tumors; however, bibliometric studies examining the correla...