Deep-learning model predicts how fruit flies form, cell by cell
The approach could apply to more complex tissues and organs, helping researchers to identify early signs of disease.
Imaging
Checking the quality of materials just got easier with a new AI tool
Acting as a “virtual spectrometer,” SpectroGen generates spectroscopic data in any modality, such as X-ray or infrared, to quickly assess a material’s quality.
Read MoreNew AI system could accelerate clinical research
By enabling rapid annotation of areas of interest in medical images, the tool can help scientists study new treatments or map disease progression.
Read MoreMachine-learning tool gives doctors a more detailed 3D picture of fetal health
MIT CSAIL researchers developed a tool that can model the shape and movements of fetuses in 3D, potentially assisting doctors in finding abnormalities and making diagnoses.
Read MoreMaking AI models more trustworthy for high-stakes settings
A new method helps convey uncertainty more precisely, which could give researchers and medical clinicians better information to make decisions.
Read MoreThe framework helps clinicians choose phrases that more accurately reflect the likelihood that certain conditions are present in X-rays.
Read MoreNew AI tool generates realistic satellite images of future flooding
The method could help communities visualize and prepare for approaching storms.
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AI pareidolia: Can machines spot faces in inanimate objects?
New dataset of “illusory” faces reveals differences between human and algorithmic face detection, links to animal face recognition, and a formula predicting where people most often perceive faces.
Read MoreA fast and flexible approach to help doctors annotate medical scans
“ScribblePrompt” is an interactive AI framework that can efficiently highlight anatomical structures across different medical scans, assisting medical workers to delineate regions of interest and abnormalities.
Read MoreNew open-source tool helps to detangle the brain
The software tool NeuroTrALE is designed to quickly and efficiently process large amounts of brain imaging data semi-automatically.
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