At AACR, Guardant Health and a Japanese group showcased data on machine learning models that predict the tissue of origin in cancers of unknown primary.

Instead of a few lab tests, thousands or even millions of molecular features can be measured simultaneously from a single patient with today’s technologies. With the right tools, this mass of data ...

Sam Altman, OpenAI’s CEO and the public face of ChatGPT, has carved out an image for himself as one of the preeminent AI whisperers of our age, whose influence supposedly extends to the White House on ...

A machine learning model that analyzes patient demographics, electronic health record data, and routine blood test results predicted a patient's risk of hepatocellular carcinoma (HCC), the most common ...

Bottom line: A machine learning model that analyzes patient demographics, electronic health record data, and routine blood test results predicted a patient's risk of hepatocellular carcinoma (HCC), ...

A free open-access webinar will introduce the Cancer Genome Interpreter (CGI), an advanced bioinformatics tool to interpret mutations in cancer genomes developed by IRB Barcelona and co-created with ...

We integrated multiple renal tubulointerstitial transcriptomic datasets from DKD and control cohorts to identify differentially expressed genes, followed by functional enrichment analysis.

Epigenetics entails reversible modifications that regulate gene activity without altering DNA. Non-coding RNA interactions and DNA methylation direct expression in response to signaling and ...

Despite advances in cancer prevention and treatment, large disparities persist in cancer mortality worldwide. Mortality-to-incidence ratios, commonly used as a proxy for cancer survival, remain ...

Machine Learning Model for Predicting Severe Adverse Events in Oncology Patients Using the US Food and Drug Administration Adverse Event Reporting System ClinBioNGS is a modular, fully containerized ...