过去十年间，机器学习在医学领域扮演着日益重要的角色。然而，许多正在开发和部署的最先进模型缺乏透明度，限制了其融入临床决策过程，并引发了对患者安全的担忧。在此，研究人员呼吁关注符号回归（symbolic regression, SR）——一种在很大程度上被忽视的 ...

A curated collection of papers, benchmarks, surveys, and tools for model quantization, covering low-bit networks, LLMs, multimodal and generative models, vector and lattice quantization, and efficient ...

Spread the loveLook, the writing’s on the wall, isn’t it? Artificial intelligence isn’t some distant sci-fi fantasy anymore; it’s here, it’s transforming industries, and frankly, it’s reshaping the ...

Deep neural networks (DNNs) are a class of artificial neural networks (ANNs) that are deep in the sense that they have many layers of hidden units between the input and output layers. Deep neural ...

Spread the loveLook, the future isn’t just coming; it’s already here, and it’s humming with artificial intelligence. We’re ...

Researchers in Türkiye combined transfer learning with MobileNetV2, Xception, and classical classifiers to classify five rice ...

Ben Affleck is going viral for his deep knowledge of AI, from neural networks and transformers to open weights. The actor, who sold his AI filmmaking startup to Netflix earlier this year, is proving ...

A new PLOS Digital Health study shows that machine learning models trained on a 15-item questionnaire can screen adults for ...

There are effective approaches for 2D segmentation, yet 3D cell segmentation remains a critical bottleneck due to diverse cell morphologies, low signal-to-noise ratios, and data scarcity. We introduce ...

We began this series with a simple question: why should someone already fluent in Python bother learning SageMath? Fourteen ...

The Monte Carlo method is a computational technique that uses random numbers to repeat trials and find solutions or ...

Background Hereditary transthyretin amyloidosis (ATTRv) is a rare multisystem disorder with marked phenotypic heterogeneity.