Results 31 to 40 of about 329,541 (261)
Unleashing the Power of Machine Learning in Nanomedicine Formulation Development
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore +7 more
wiley +1 more source
This review explores advances in wearable and lab‐on‐chip technologies for breast cancer detection. Covering tactile, thermal, ultrasound, microwave, electrical impedance tomography, electrochemical, microelectromechanical, and optical systems, it highlights innovations in flexible electronics, nanomaterials, and machine learning.
Neshika Wijewardhane +4 more
wiley +1 more source
Optimizing quantum gates towards the scale of logical qubits
A foundational assumption of quantum error correction theory is that quantum gates can be scaled to large processors without exceeding the error-threshold for fault tolerance.
Paul V. Klimov +23 more
doaj +1 more source
Detecting shortcut learning for fair medical AI using shortcut testing
Machine learning (ML) holds great promise for improving healthcare, but it is critical to ensure that its use will not propagate or amplify health disparities.
Alexander Brown +5 more
doaj +1 more source
A soft robotic simulator is developed to replicate the digital removal of feces (DRF), a sensitive yet essential nursing procedure. Integrating soft actuators, sensors, and a realistic rectal model, the simulator balances functional fidelity with perceptual realism. Engineering evaluations and nurse feedback confirm its potential to enhance training in
Shoko Miyagawa +10 more
wiley +1 more source
Dimethylsulfoniopropionate (DMSP) is a major marine organosulfur compound central to climate‐relevant dimethyl sulfide (DMS) production. In Halomonas sp. D47, DMSP catabolism is revealed to be coordinated by two transcriptional regulators, AcuR and AcuZ, which control gene expression by sensing DMSP and its metabolites.
Li‐Yuan Zheng +16 more
wiley +1 more source
Time-Aware Language Models as Temporal Knowledge Bases
Many facts come with an expiration date, from the name of the President to the basketball team Lebron James plays for. However, most language models (LMs) are trained on snapshots of data collected at a specific moment in time.
Bhuwan Dhingra +5 more
doaj +1 more source
De Novo Multi‐Mechanism Antimicrobial Peptide Design via Multimodal Deep Learning
Current AI‐driven peptide discovery often overlooks complex structural data. This study presents M3‐CAD, a generative pipeline that leverages 3D voxel coloring and a massive database of over 12 000 peptides to capture nuanced physicochemical contexts.
Xiaojuan Li +23 more
wiley +1 more source
Transforming wearable data into personal health insights using large language model agents
Deriving personalized insights from popular wearable trackers requires complex numerical reasoning that challenges standard LLMs, necessitating tool-based approaches like code generation.
Mike A. Merrill +19 more
doaj +1 more source
Caravan - A global community dataset for large-sample hydrology
High-quality datasets are essential to support hydrological science and modeling. Several CAMELS (Catchment Attributes and Meteorology for Large-sample Studies) datasets exist for specific countries or regions, however these datasets lack standardization,
Frederik Kratzert +11 more
doaj +1 more source

