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Lung cancer is highly fatal, largely due to late diagnoses, but early detection can greatly improve survival. This study developed three models to enhance early diagnosis: an MLP for clinical data, a CNN for imaging data, and a hybrid model combining both.

The authors test the effectiveness of machine learning to predict onset of cardiovascular disease.

In this article the authors created an interaction map of proteins involved in colorectal cancer to look for driver vs. non-driver genes. That is they wanted to see if they could determine what genes are more likely to drive the development and progression in colorectal cancer and which are present in altered states but not necessarily driving disease progression.

The authors looked at 5-FU resistant HeLa cells and the ability of an herbal extract to show anti-inflammatory properties.

Machine learning algorithms are becoming increasingly popular for data crunching across a vast area of scientific disciplines. Here, the authors compare two machine learning algorithms with respect to accuracy and user-friendliness and find that random forest algorithms outperform logistic regression when applied to the same dataset.

Antibiotics are used to treat dangerous diseases. Over time, however, bacteria are becoming resistant to antibiotics - which poses a threat to humans and animals alike. In this paper, the authors examine how E. coli gains resistance to the antibiotic amoxicillin.

Human intelligence is correlated with variation in the protein neuroplastin-65, which is encoded by the NPTN gene. The authors examine the evolution of this gene across different animal species.

Investigating the green valley hypotheses of galaxy evolution

In this study, the authors studied the ability for bacteria to develop antibiotic resistance over successive generations and modeled the trajectory to predict how antibiotic resistance is developed.

Many species of trees are distributed widely around the world, though not always in a way that makes immediate sense. The authors here use genetic information to help explain the geographic distribution of various conifer species throughout the world.