AI Medical Compendium Journal:
Proceedings of the National Academy of Sciences of the United States of America

Showing 21 to 30 of 332 articles

Learning-based inference of longitudinal image changes: Applications in embryo development, wound healing, and aging brain.

Proceedings of the National Academy of Sciences of the United States of America
Longitudinal imaging data are routinely acquired for health studies and patient monitoring. A central goal in longitudinal studies is tracking relevant change over time. Traditional methods remove nuisance variation with custom pipelines to focus on ...

Fast Interpretable Greedy-Tree Sums.

Proceedings of the National Academy of Sciences of the United States of America
Modern machine learning has achieved impressive prediction performance, but often sacrifices interpretability, a critical consideration in high-stakes domains such as medicine. In such settings, practitioners often use highly interpretable decision t...

AI protocol for retrieving protein dynamic structures from two-dimensional infrared spectra.

Proceedings of the National Academy of Sciences of the United States of America
Understanding the dynamic evolution of protein structures is crucial for uncovering their biological functions. Yet, real-time prediction of these dynamic structures remains a significant challenge. Two-dimensional infrared (2DIR) spectroscopy is a p...

A deep learning-enabled smart garment for accurate and versatile monitoring of sleep conditions in daily life.

Proceedings of the National Academy of Sciences of the United States of America
In wearable smart systems, continuous monitoring and accurate classification of different sleep-related conditions are critical for enhancing sleep quality and preventing sleep-related chronic conditions. However, the requirements for device-skin cou...

Machine learning-enhanced surface-enhanced spectroscopic detection of polycyclic aromatic hydrocarbons in the human placenta.

Proceedings of the National Academy of Sciences of the United States of America
The detection and identification of polycyclic aromatic hydrocarbons (PAHs) and their derivatives, polycyclic aromatic compounds (PACs), are essential for environmental and health monitoring, for assessing toxicological exposure and their associated ...

Deep learning-driven bacterial cytological profiling to determine antimicrobial mechanisms in .

Proceedings of the National Academy of Sciences of the United States of America
Tuberculosis (TB), caused by , remains a significant global health threat, affecting an estimated 10.6 million people in 2022. The emergence of multidrug resistant and extensively drug resistant strains necessitates the development of novel and effec...

Multiorifice acoustic microrobot for boundary-free multimodal 3D swimming.

Proceedings of the National Academy of Sciences of the United States of America
The emerging new generation of small-scaled acoustic microrobots is poised to expedite the adoption of microrobotics in biomedical research. Recent designs of these microrobots have enabled intricate bioinspired motions, paving the way for their real...

Random noise promotes slow heterogeneous synaptic dynamics important for robust working memory computation.

Proceedings of the National Academy of Sciences of the United States of America
Recurrent neural networks (RNNs) based on model neurons that communicate via continuous signals have been widely used to study how cortical neural circuits perform cognitive tasks. Training such networks to perform tasks that require information main...

3D electron microscopy for analyzing nanoparticles in the tumor endothelium.

Proceedings of the National Academy of Sciences of the United States of America
Delivering medical agents to diseased tissues has been challenging, leading researchers to study the in vivo transport process in the body for improving delivery. Many imaging techniques exist for mapping the distribution of medical agent-carrying na...

Correlating enzymatic reactivity for different substrates using transferable data-driven collective variables.

Proceedings of the National Academy of Sciences of the United States of America
Machine learning (ML) is transforming the investigation of complex biological processes. In enzymatic catalysis, one significant challenge is identifying the reactive conformations (RC) of the enzyme:substrate complex where the substrate assumes a pr...