New framework renders AI more trustworthy for cancer subtyping

Medical artificial intelligence (AI) faces a fundamental challenge: uncertainty quantification. Artificial neural networks ...

Quantum-inspired AI could tailor patients' cancer treatment to their entire molecular background

For a child diagnosed with neuroblastoma—the most common infant cancer, occurring when early nerve cells grow out of ...
News-Medical.Net

New human protein atlas maps how cancer rewires the body’s tissues

Researchers created a DIA-MS atlas of 13,609 proteins across 2,856 samples from fetal, healthy adult, paired non-tumor, and ...
News-Medical.Net

AI accurately measures mesothelioma tumors for better treatment decisions

Physicians and researchers at the Netherlands Cancer Institute have developed an AI model that outperforms physicians at ...
GitHub

BreastDCEDL - 2,072 Breast Cancer Patients

The MinCrop version provides three methodicaly selected DCE-MRI time points (pre-contrast, early post-contrast, late post-contrast) cropped to 256×256 pixels around the main tumor. This version has ...
IEEE

Combining Features of Support Vector Machine with Convolutional Neural Network for Image Classification

Abstract: For image classification, it's recommended to start with traditional machine learning techniques before moving to deep learning. Support Vector Machine(SVM) is widely used in pattern ...
GitHub

In silico labeling: Predicting fluorescent labels in unlabeled images

This is the code for In silico labeling: Predicting fluorescent labels in unlabeled images. It is the result of a collaboration between Google Accelerated Science and two external labs: the Lee Rubin ...
Nature

MLOmics: Cancer Multi-Omics Database for Machine Learning

Framing the investigation of diverse cancers as a machine learning problem has recently shown significant potential in multi-omics analysis and cancer research. Empowering these successful machine ...
IEEE

Harnessing Deep Learning for Precise Diagnosis of 6 types of Cancers

Abstract: The use of deep learning in cancer detection has the potential to lead to more precise and timely diagnosis. In order to identify cancer, this study presents a deep learning-based picture ...
Nature

FastMRI Prostate: A public, biparametric MRI dataset to advance machine learning for prostate cancer imaging

Magnetic resonance imaging (MRI) has experienced remarkable advancements in the integration of artificial intelligence (AI) for image acquisition and reconstruction. The availability of raw k-space ...
Frontiers

A breast cancer-specific combinational QSAR model development using machine learning and deep learning approaches

Breast cancer is the most prevalent and heterogeneous form of cancer affecting women worldwide. Various therapeutic strategies are in practice based on the extent of disease spread, such as surgery, ...
The Lancet

A radiomics-based decision support tool improves lung cancer diagnosis in combination with the Herder score in large lung nodules

cDepartment of Respiratory Medicine, Charing Cross Hospital, Imperial College Healthcare Trust, Fulham Palace Road, London, W6 8RF, UK dDepartment of Respiratory Medicine, University College London ...