We show that, compared with surgeon predictions and existing risk-prediction tools, our machine-learning model can enhance ...

Researchers have developed a powerful new software toolbox that allows realistic brain models to be trained directly on data.

The experimental model won't compete with the biggest and best, but it could tell us why they behave in weird ways—and how ...

The TRM takes a different approach. Jolicoeur-Martineau was inspired by a technique known as the hierarchical reasoning model ...

The gpt-oss models are being tested for use on sensitive military computers. But some defense insiders say that OpenAI is ...

This study presents a phase-field crystal model that simulates AB-BA transitions in bilayer graphene, highlighting defect ...

You will be redirected to our submission process. In the field of data science and engineering, tensors have become an ...

In her ASA Footnotes article, “Meeting the Moment: Why We Can’t Afford to Let Sociology Classrooms Become Places Where Hope Comes to Die,” Ashley C. Rondini (Franklin & Marshall College) points to ...

An artificial intelligence (AI) algorithm may allow clinicians to predict risk of keratoconus progression with more than 90% accuracy, according to a retrospective study. Using data from the second ...

Eli Lilly And Company ((LLY)) announced an update on their ongoing clinical study. Take advantage of TipRanks Premium at 50% off! Unlock powerful investing tools, advanced data, and expert analyst ...

Abstract: This paper uses the cumulative prospect theory to describe the uncertainty of link impedance caused by demand changes, and introduces the prospect value to evaluate the value of each path in ...

Abstract: In this paper, a multi-objective assignment problem is studied, in which two objectives, i.e., the profit and the consumed time, are considered. Due to the uncertainty of the real life, it ...