A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...

Dengue and chikungunya, the two mosquito-borne diseases that frequently circulate at the same time, share the same Aedes ...

Machine learning holds great promise for classifying and identifying fossils, and has recently been marshaled to identify trackmakers of dinosaur ...

AI: How does this technological revolution fit with the pharmaceutical regulators who oversee the pharmaceutical sector at ...

Background Suicide rates have increased over the last couple of decades globally, particularly in the United States and among populations with lower economic status who present at safety-net ...

Objective: To develop and validate a machine learning (ML)-based prediction model of Bethesda III nodules and create a nomogram based on the best model. Methods: We collected data on patients with ...

If you rotate an image of a molecular structure, a human can tell the rotated image is still the same molecule, but a machine-learning model might think it is a new data point. In computer science ...

Patent applications on artificial intelligence and machine learning have soared in recent years, yet legal guidance on the patentability of AI and machine learning algorithms remains scarce. The US ...

Objective: To develop and validate a machine learning (ML)-based model for predicting stroke-associated pneumonia (SAP) risk in older adult hemorrhagic stroke patients. Methods: A retrospective ...