AI Medical Compendium Topic:
Neoplasms

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Effects of Multi-Omics Characteristics on Identification of Driver Genes Using Machine Learning Algorithms.

Genes
Cancer is a complex disease caused by genomic and epigenetic alterations; hence, identifying meaningful cancer drivers is an important and challenging task. Most studies have detected cancer drivers with mutated traits, while few studies consider mul...

The stability of oncologic MRI radiomic features and the potential role of deep learning: a review.

Physics in medicine and biology
The use of MRI radiomic models for the diagnosis, prognosis and treatment response prediction of tumors has been increasingly reported in literature. However, its widespread adoption in clinics is hampered by issues related to features stability. In ...

The future of early cancer detection.

Nature medicine
A proactive approach to detecting cancer at an early stage can make treatments more effective, with fewer side effects and improved long-term survival. However, as detection methods become increasingly sensitive, it can be difficult to distinguish in...

Label-Free Differentiation of Cancer and Non-Cancer Cells Based on Machine-Learning-Algorithm-Assisted Fast Raman Imaging.

Biosensors
This paper proposes a rapid, label-free, and non-invasive approach for identifying murine cancer cells (B16F10 melanoma cancer cells) from non-cancer cells (C2C12 muscle cells) using machine-learning-assisted Raman spectroscopic imaging. Through quic...

Development and validation of a combined nomogram model based on deep learning contrast-enhanced ultrasound and clinical factors to predict preoperative aggressiveness in pancreatic neuroendocrine neoplasms.

European radiology
OBJECTIVES: This study aimed to develop and validate a combined nomogram model based on deep learning (DL) contrast-enhanced ultrasound (CEUS) and clinical factors to preoperatively predict the aggressiveness of pancreatic neuroendocrine neoplasms (P...

Effectiveness of Artificial Intelligence for Personalized Medicine in Neoplasms: A Systematic Review.

BioMed research international
PURPOSE: Artificial intelligence (AI) techniques are used in precision medicine to explore novel genotypes and phenotypes data. The main aims of precision medicine include early diagnosis, screening, and personalized treatment regime for a patient ba...

Bayesian networks elucidate complex genomic landscapes in cancer.

Communications biology
Bayesian networks (BNs) are disciplined, explainable Artificial Intelligence models that can describe structured joint probability spaces. In the context of understanding complex relations between a number of variables in biological settings, they ca...

Deep Learning in mHealth for Cardiovascular Disease, Diabetes, and Cancer: Systematic Review.

JMIR mHealth and uHealth
BACKGROUND: Major chronic diseases such as cardiovascular disease (CVD), diabetes, and cancer impose a significant burden on people and health care systems around the globe. Recently, deep learning (DL) has shown great potential for the development o...

Predicting the Survival of Cancer Patients With Multimodal Graph Neural Network.

IEEE/ACM transactions on computational biology and bioinformatics
In recent years, cancer patients survival prediction holds important significance for worldwide health problems, and has gained many researchers attention in medical information communities. Cancer patients survival prediction can be seen the classif...