---
tags:
- schemaforge
- ai-refined
- machine-learning-research
license: mit
---

# www.nature.com

Auto-refined by [SchemaForge](https://schemaforge.duckdns.org)

## Metadata
- **Topic:** Machine Learning Research
- **Quality Score:** 0.95
- **Source:** Autonomous web scraper

## Extracted Facts
- Machine learning is the ability of a machine to improve its performance based on previous results.
- Machine learning methods enable computers to learn without being explicitly programmed.
- Privacy risks from medical AI tools are not shared equally.
- Learning from routine health system data builds better neuroimaging AI models.
- A new method designs RNA sequences by learning from alignments of structurally similar molecules.
- MRICombo: a deep-learning-based framework for universal volumetric segmentation grading-staging and malignancy detection across heterogeneous MRI.
- AI-based augmentation of oncology clinical trials.
- The Virtual Tissues foundation model resolves spatial proteomics across scales.
- Divergent impacts of explainable AI for dermatological diagnosis on clinicians versus lay people.
- Automatic report-based assessment of radiology-pathology concordance in surgical patients using BERT and DPCNN.
- AI agents are checking the scientific literature — and spotting decades-old errors.
- Privacy attacks can reveal whether someone’s medical data was used to train an AI model.