AI Medical Compendium Journal:
Nature communications

Showing 101 to 110 of 854 articles

Prompt injection attacks on vision language models in oncology.

Nature communications
Vision-language artificial intelligence models (VLMs) possess medical knowledge and can be employed in healthcare in numerous ways, including as image interpreters, virtual scribes, and general decision support systems. However, here, we demonstrate ...

Self-rerouting sensor network for electronic skin resilient to severe damage.

Nature communications
We propose a network architecture for electronic skin with an extensive sensor array-crucial for enabling robots to perceive their environment and interact effectively with humans. Fault tolerance is essential for electronic skins on robot exteriors....

Monolithic electrostatic actuators with independent stiffness modulation.

Nature communications
Robotic artificial muscles, inspired by the adaptability of biological muscles, outperform rigid robots in dynamic environments due to their flexibility. However, the intrinsic compliance of the soft actuators restricts force transmission capacity an...

Intricacies of human-AI interaction in dynamic decision-making for precision oncology.

Nature communications
AI decision support systems can assist clinicians in planning adaptive treatment strategies that can dynamically react to individuals' cancer progression for effective personalized care. However, AI's imperfections can lead to suboptimal therapeutics...

STAIG: Spatial transcriptomics analysis via image-aided graph contrastive learning for domain exploration and alignment-free integration.

Nature communications
Spatial transcriptomics is an essential application for investigating cellular structures and interactions and requires multimodal information to precisely study spatial domains. Here, we propose STAIG, a deep-learning model that integrates gene expr...

Application of machine learning and genomics for orphan crop improvement.

Nature communications
Orphan crops are important sources of nutrition in developing regions and many are tolerant to biotic and abiotic stressors; however, modern crop improvement technologies have not been widely applied to orphan crops due to the lack of resources avail...

Dendrites endow artificial neural networks with accurate, robust and parameter-efficient learning.

Nature communications
Artificial neural networks (ANNs) are at the core of most Deep Learning (DL) algorithms that successfully tackle complex problems like image recognition, autonomous driving, and natural language processing. However, unlike biological brains who tackl...

iDIA-QC: AI-empowered data-independent acquisition mass spectrometry-based quality control.

Nature communications
Quality control (QC) in mass spectrometry (MS)-based proteomics is mainly based on data-dependent acquisition (DDA) analysis of standard samples. Here, we collect 2754 files acquired by data independent acquisition (DIA) and paired 2638 DDA files fro...

Accelerated enzyme engineering by machine-learning guided cell-free expression.

Nature communications
Enzyme engineering is limited by the challenge of rapidly generating and using large datasets of sequence-function relationships for predictive design. To address this challenge, we develop a machine learning (ML)-guided platform that integrates cell...

Predicting metabolite response to dietary intervention using deep learning.

Nature communications
Due to highly personalized biological and lifestyle characteristics, different individuals may have different metabolite responses to specific foods and nutrients. In particular, the gut microbiota, a collection of trillions of microorganisms living ...