Machine learning methods for small data challenges in molecular science
Small data are often used in scientific and engineering research due to the presence of
various constraints, such as time, cost, ethics, privacy, security, and technical limitations in …
various constraints, such as time, cost, ethics, privacy, security, and technical limitations in …
Human-in-the-loop machine learning: a state of the art
Researchers are defining new types of interactions between humans and machine learning
algorithms generically called human-in-the-loop machine learning. Depending on who is in …
algorithms generically called human-in-the-loop machine learning. Depending on who is in …
Cellpose 2.0: how to train your own model
Pretrained neural network models for biological segmentation can provide good out-of-the-
box results for many image types. However, such models do not allow users to adapt the …
box results for many image types. However, such models do not allow users to adapt the …
Ambiguity-selective consistency regularization for mean-teacher semi-supervised medical image segmentation
Semi-supervised learning has greatly advanced medical image segmentation since it
effectively alleviates the need of acquiring abundant annotations from experts, wherein the …
effectively alleviates the need of acquiring abundant annotations from experts, wherein the …
Artificial general intelligence for medical imaging analysis
Large-scale Artificial General Intelligence (AGI) models, including Large Language Models
(LLMs) such as ChatGPT/GPT-4, have achieved unprecedented success in a variety of …
(LLMs) such as ChatGPT/GPT-4, have achieved unprecedented success in a variety of …