A new machine learning model developed by The George Institute for Global Health can successfully predict heart disease risk in women by analyzing mammograms. The findings were published today in ...

Researchers developed and validated a new lung cancer prediction model, Sybil-Epi, by integrating clinical and epidemiologic data with a pre-existing model.

Assessing mortality trends among patients with lip and oral cavity cancer due to tobacco consumption: A systematic analysis of the Global Burden of Disease-2021.

Researchers have proposed an integrated eco-driving framework for fuel cell hybrid electric vehicles in multi-lane highway ...

OAK BROOK, Ill. – An artificial intelligence (AI) deep learning tool that estimates the malignancy risk of lung nodules achieved high cancer detection rates while significantly reducing false-positive ...

Scientists have developed a geometric deep learning method that can create a coherent picture of neuronal population activity during cognitive and motor tasks across experimental subjects and ...

After uncovering a unifying algorithm that links more than 20 common machine-learning approaches, researchers organized them into a 'periodic table of machine learning' that can help scientists ...

Characterizing the clinical and genomic features of androgen indifferent prostate cancer. Distribution of manual p53 scores (rows) and automated digital image analysis (DIA) p53 scores (columns) by ...