Results 161 to 170 of about 57,852 (256)

Reconfigurable Au Nanoparticle Monolayers on Regenerated Cellulose Hydrogels: Highly Sensitive SERS Detection of Polystyrene Micro/Nanoplastics With Interpretable Deep Learning

Advanced Functional Materials, EarlyView.
A regenerated cellulose (RC) hydrogel‐based SERS substrate integrating a Marangoni‐transferred gold nanoparticle self‐assembled monolayer (Au‐SAM) is fabricated. Reswelling‐induced hotspot formation enhances polystyrene micro/nanoplastics (PS MNPs) detection in complex matrices, providing reproducible, high‐throughput SERS signals across diverse ...
Youngho Jeon, Yu‐Jin Jeon, Suji Lee, Jeseong Kim, Dae‐Hyun Jung, Jungmok You   +5 more
wiley   +1 more source

Revealing GRK5 Activation Features by Interpretable Machine Learning and Molecular Dynamics Simulation. [PDF]

Int J Mol Sci
Song Y, Kong M, Zhang F, Pu X.
europepmc   +1 more source

Wearable Kirigami‐Apertured Capacitive Sensors for Continuous Cardiac Volumetric Monitoring

Advanced Functional Materials, EarlyView.
A wearable kirigami‐apertured carbon nanotube‐paper composite (K‐CPC) capacitive sensor enables cardiac volumetric monitoring. The kirigami process creates a central aperture with cantilevered fibers that confine the electric field, enhancing both sensitivity and lateral resolution.
Yu‐Jen Cheng, Shawn Kim, Jonathan Avery, Younghoon Kwon, Jae‐Hyun Chung   +4 more
wiley   +1 more source

An interpretable machine learning model for predicting stroke in patients with hypertension: insights from the SPRINT. [PDF]

Sci Rep
Han J, Lin L, Zhao T, Zhang Y, Zhao Z, Wang W, Feng R, Ding Y, Zeng Y.   +8 more
europepmc   +1 more source

High‐Throughput Discovery of Quantum Frustrated Materials

Advanced Functional Materials, EarlyView.
Physics‐guided discovery of frustrated kagome and triangular magnets. ABSTRACT Geometrical frustration provides a fertile platform for realizing exotic quantum phases such as spin liquids, yet, the predictive identification of frustrated magnets remains limited.
Byeong‐Hyeon Jeong, Hee Seung Kim, Jiwon Choi, SungBin Lee, Myung Joon Han   +4 more
wiley   +1 more source

Interpretable machine learning-based real-time sepsis diagnosis. [PDF]

Sci Rep
Mahmud F, Quamruzzaman M, Sanka AI, Cheung RCC, Chowdhury MH.   +4 more
europepmc   +1 more source

Intelligent Orthopedics: Machine Learning in Diagnosis of Bone Disease, Implants, and Bone Health Monitoring

Advanced Healthcare Materials, EarlyView.
Efficient recovery from traumatic or degenerative diseases is a great challenge, even after all the advancements in bone and cartilage regeneration. Machine learning (ML) algorithms have presented opportunities to enhance these aspects by accurately analyzing imaging data.
Maryam Kamaei, Hesam Mohammadi, Shamim Golafshan, Mojtaba Alehosseini, Mahsa Mohammadzadeh, Atefeh Golshirazi, Nasim Golafshan, Tatiane Eufrásio‐da‐Silva, Alireza Dolatshahi‐Pirouz, Gorka Orive   +9 more
wiley   +1 more source

Anomaly detection of fermi surface morphology in Co2MnGaxGe1-x via interpretable machine learning. [PDF]

Sci Rep
Ishikawa D, Fuku K, Miura Y, Igarashi Y, Iwasaki Y, Sakuraba Y, Yaji K, Foggiatto AL, Yamazaki T, Nagamura N, Kotsugi M.   +10 more
europepmc   +1 more source

Stability of Medicinal Nanoemulsions to Spaceflight: Insights From the StarMed Experiment

Advanced Healthcare Materials, EarlyView.
Chitosan‐coated melatonin nanoemulsions (MN) recovered from a sounding rocket mission preserve droplet size and controlled‐release behavior, whereas uncoated nanoemulsions show ageing‐driven droplet growth and increased accessible drug fraction. Simple polymer coatings thus enhance the flight resilience of liquid space medicines under cumulative launch
Modupe Adebowale, Nguyen Van Duc Long, Philip M. Williams, Jens Hauslage, Volker Hessel   +4 more
wiley   +1 more source

Integration of intraoperative data in interpretable machine learning models to predict postoperative AKI in noncardiac surgery patients. [PDF]

JAMIA Open
Do J, Shah KH, Xu MC, Kim AH, Suresh V, Guggilla N, Li M, Kothari R.   +7 more
europepmc   +1 more source