Results 161 to 170 of about 279,520 (289)

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

Automated meningioma detection using skull X ray images with deep learning and machine learning classifiers. [PDF]

Sci Rep
Kim HU, Choi Y, Kim YS, Kim YI, Yoon WS, Yang SH.   +5 more
europepmc   +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

Identification of Potential Biomarkers in Prostate Cancer Microarray Gene Expression Leveraging Explainable Machine Learning Classifiers. [PDF]

Cancers (Basel)
Marouf AA, Rokne JG, Alhajj R.
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

Early classification of functional connectomes in Parkinson's disease: a comparison of machine learning classifiers using multi-scale topological features. [PDF]

BMC Med Inform Decis Mak
Donisi L, Micco R, Pirozzi MA, Siciliano M, Franza F, Pisani N, Zamir B, Cirillo M, Tessitore A, Esposito F.   +9 more
europepmc   +1 more source

Characterisation of Cognitive Load Using Machine Learning Classifiers of Electroencephalogram Data. [PDF]

Sensors (Basel), 2023
Wang Q, Smythe D, Cao J, Hu Z, Proctor KJ, Owens AP, Zhao Y.   +6 more
europepmc   +1 more source

Unlocking the Potential of MXene‐Based Electrochemical Biosensors: A Review of Biofunctionalization Strategies and Biosensing Principles

Advanced Materials Technologies, EarlyView.
ABSTRACT Electrochemical biosensors enable the accurate and timely detection of clinical biomarkers, improving healthcare and precision medicine. MXene nanosheets, a class of 2D transition metal carbides, nitrides, and carbonitrides, are promising materials for developing next‐generation electrochemical biosensors due to their unique physicochemical ...
Muhsin Ali, Sharat Chandra Barman, Isobel Steer, Aya H. Alshareef, Dana Alsulaiman   +4 more
wiley   +1 more source

Ultraconserved Elements and Machine Learning Classifiers Enable Robust Phylogenetics and Taxonomy in Model and Non-Model Nematodes. [PDF]

Mol Ecol Resour
Villegas L, Jimenez L, van der Sprong J, Holovachov O, Waldvogel AM, Schiffer PH.   +5 more
europepmc   +1 more source

Classifying Performance Bounds Using Machine Learning

Traditional performance analysis tools, such as the Roofline model, require visual interpretation to determine performance bounds. For CPUs which have complex cache hierarchies and front-end out-of-order capabilities—that is the CPUs we use for high performance computing—accurately identifying the true performance bound is challenging. This work is the
Littman, Lewis, Deakin, Tom
openaire   +1 more source