AIMC Topic: Neoplasms

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Predicting intratumoral fluid pressure and liposome accumulation using physics informed deep learning.

Scientific reports
Liposome-based anticancer agents take advantage of the increased vascular permeability and transvascular pressure gradients for selective accumulation in tumors, a phenomenon known as the enhanced permeability and retention(EPR) effect. The EPR effec...

Operational greenhouse-gas emissions of deep learning in digital pathology: a modelling study.

The Lancet. Digital health
BACKGROUND: Deep learning is a promising way to improve health care. Image-processing medical disciplines, such as pathology, are expected to be transformed by deep learning. The first clinically applicable deep-learning diagnostic support tools are ...

Explainable deep learning for tumor dynamic modeling and overall survival prediction using Neural-ODE.

NPJ systems biology and applications
While tumor dynamic modeling has been widely applied to support the development of oncology drugs, there remains a need to increase predictivity, enable personalized therapy, and improve decision-making. We propose the use of Tumor Dynamic Neural-ODE...

Big data and artificial intelligence in cancer research.

Trends in cancer
The field of oncology has witnessed an extraordinary surge in the application of big data and artificial intelligence (AI). AI development has made multiscale and multimodal data fusion and analysis possible. A new era of extracting information from ...

Education by a social robot on nutrition and catheter care in pediatric oncology patients.

Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer
PURPOSE: To improve knowledge on nutrition and catheter care in children with cancer by an educational intervention with a social robot.

An embedded feature selection method based on generalized classifier neural network for cancer classification.

Computers in biology and medicine
The selection of relevant genes plays a vital role in classifying high-dimensional microarray gene expression data. Sparse group Lasso and its variants have been employed for gene selection to capture the interactions of genes within a group. Most of...

From cancer big data to treatment: Artificial intelligence in cancer research.

The journal of gene medicine
In recent years, developing the idea of "cancer big data" has emerged as a result of the significant expansion of various fields such as clinical research, genomics, proteomics and public health records. Advances in omics technologies are making a si...

A survey on cancer detection via convolutional neural networks: Current challenges and future directions.

Neural networks : the official journal of the International Neural Network Society
Cancer is a condition in which abnormal cells uncontrollably split and damage the body tissues. Hence, detecting cancer at an early stage is highly essential. Currently, medical images play an indispensable role in detecting various cancers; however,...

Prediction of cancer recurrence based on compact graphs of whole slide images.

Computers in biology and medicine
Cancer recurrence is one of the primary causes of patient mortality following treatment, indicating increased aggressiveness of cancer cells and difficulties in achieving a cure. A critical step to improve patients' survival is accurately predicting ...