Results 171 to 180 of about 610,735 (230)

From the Discovery of the Giant Magnetocaloric Effect to the Development of High‐Power‐Density Systems

Advanced Materials Technologies, EarlyView.
The article overviews past and current efforts on caloric materials and systems, highlighting the contributions of Ames National Laboratory to the field. Solid‐state caloric heat pumping is an innovative method that can be implemented in a wide range of cooling and heating applications.
Agata Czernuszewicz, Yaroslav Mudryk, Jun Cui, Lucas Griffith, Duane D. Johnson, Julie Slaughter   +5 more
wiley   +1 more source

Interpretable machine learning in type-2 diabetes prediction in patients with depressive symptoms: Insights from mendelian randomization and physical activity. [PDF]

Sci Prog
Li Z, Qiu X, Wu W, Kang H.
europepmc   +1 more source

Hydrogel‐Based 3D‐Printable Stretchable Pressure Sensor

Advanced Materials Technologies, EarlyView.
We present a carbon‐black‐functionalized double‐network granular hydrogel (DNGH) pressure sensor capable of detecting pressures from 200 Pa, equivalent to a light finger touch, up to 500 kPa. The sensor exhibits signal drifts below 3.5% after 800 cycles and response times around 80 ms. Leveraging this broad sensing range, we 3D print this material into
Tianyu Yuan, Chenzhuo Li, Antonia Georgopoulou, John M. Kolinski, Esther Amstad   +4 more
wiley   +1 more source

End‐to‐End Sensing Systems for Breast Cancer: From Wearables for Early Detection to Lab‐Based Diagnosis Chips

Advanced Materials Technologies, EarlyView.
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, Lyn I. Jones, Richard M. Martin, Helen Winter, Faezeh Arab Hassani   +4 more
wiley   +1 more source

Transducers Across Scales and Frequencies: A System‐Level Framework for Multiphysics Integration and Co‐Design

Advanced Materials Technologies, EarlyView.
Transducers convert physical signals into electrical and optical representations, yet each mechanism is bounded by intrinsic trade‐offs across bandwidth, sensitivity, speed, and energy. This review maps transduction mechanisms across physical scale and frequency, showing how heterogeneous integration and multiphysics co‐design transform isolated ...
Aolei Xu, Mengyao Xiao, Zhouli Sui, Yinpeng Wang, Daoye Zheng, Yuxin Liu, Luwei Wang, Huajun Liu, Chengkuo Lee   +8 more
wiley   +1 more source

Editorial: Machine learning algorithms for brain imaging: new frontiers in neurodiagnostics and treatment. [PDF]

Front Neuroinform
Tandle A, Appukuttan S, Honari H.
europepmc   +1 more source

Characterization of Droplet Formation in Ultrasonic Spray Coating: Influence of Ink Formulation Using Phase Doppler Anemometry and Machine Learning

Advanced Materials Technologies, EarlyView.
This study explores how machine learning models, trained on small experimental datasets obtained via Phase Doppler Anemometry (PDA), can accurately predict droplet size (D32) in ultrasonic spray coating (USSC). By capturing the influence of ink complexity (solvent, polymer, nanoparticles), power, and flow rate, the model enables precise droplet control
Pieter Verding, Danny E. P. Vanpoucke, Yunus T. Aksoy, Tobias Corthouts, Maria R. Vetrano, Wim Deferme   +5 more
wiley   +1 more source

Machine Learning in Predicting the Risk of Esophagogastric Variceal Bleeding Among Patients With Liver Cirrhosis: Systematic Review and Meta-Analysis.

J Med Internet Res
Lian Y, Qiu X, Wang G, Liu N, Zhao J, Song S, Wang S, Sun M.   +7 more
europepmc   +1 more source

Respiratory Signal Processing and Analysis Using Flexible Capacitive Sensor Data

Advanced Materials Technologies, EarlyView.
Capacitive pressure sensors based on poly(glycerol sebacate) (PGS) substrates are developed for continuous, non‐invasive respiratory monitoring. Integrated with a signal processing algorithm, they enable accurate tracking of thoracic expansion and retraction.
Bernardo A. Vicente, Raquel Sebastião, Alda Marques, Vitor Sencadas   +3 more
wiley   +1 more source

Accuracy of Radiomics-Based Machine Learning for Predicting Risk of Recurrence in Non-Small Cell Lung Cancer: Systematic Review and Meta-Analysis.

J Med Internet Res
Wu J, Zhang Y, Wang J, Chen C, Hu S, Chen W.   +5 more
europepmc   +1 more source