A deep learning model using retinal images obtained during retinopathy of prematurity (ROP) screening may be used to predict diagnosis of bronchopulmonary dysplasia (BPD) and pulmonary hypertension ...

Artificial Intelligence (AI) is revolutionizing the dynamics of technological advancement in the field of medical imaging, ...

Study in a Sentence: Cedars-Sinai researchers are developing KronosRx, an artificial intelligence-powered platform that uses human-derived organoids and deep-learning models to forecast adverse drug ...

Physiologically Based Pharmacokinetic Model to Assess the Drug-Drug-Gene Interaction Potential of Belzutifan in Combination With Cyclin-Dependent Kinase 4/6 Inhibitors A total of 14,177 patients were ...

Database optimization has long relied on traditional methods that struggle with the complexities of modern data environments. These methods often fail to efficiently handle large-scale data, complex ...

BiLSTM, an ICD-11 automatic coding model using MC-BERT and label attention. Experiments on clinical records show 83.86% ...

Overview: Master deep learning with these 10 essential books blending math, code, and real-world AI applications for lasting ...

Why is a Chinese quant shop behind one of the world’s strongest open-weight LLMs? It turns out that modern quantitative investing and frontier AI labs are converging on the same institutional machine: ...

Deep learning models have shown great potential in predicting and engineering functional enzymes and proteins. Does this prowess extend to other fields of biology as well? Subscribe to our newsletter ...

Artificial intelligence was built to process data, not to think like us. Yet a growing body of research is finding that the internal workings of advanced language and speech models are starting to ...