Results 171 to 180 of about 2,065,553 (347)

Intelligent Eye Tracker Integrated with Cylindrical Capacitive Sensors for Chronic Fatigue Assessment

Advanced Sensor Research, EarlyView.
A wearable capacitive eye tracker for chronic fatigue assessment is presented, utilizing cylindrically shaped capacitive sensors made of a carbon nanotube‐paper composite. By integrating a novel fatigue‐induction protocol with machine learning, the device achieves 0.75‐sensitivity and 0.73‐specificity, providing a practical alternative to existing ...
Tianyi Li, Seo‐Hyun Park, Changwoo Lee, Shawn Kim, Younghoon Kwon, Hojun Kim, Jae‐Hyun Chung   +6 more
wiley   +1 more source

Machine Learning Enhanced Multimodal Bioelectronics: Advancement Toward Intelligent Healthcare Systems

Advanced Sensor Research, EarlyView.
This review examines recent advancements in multimodal bioelectronics, emphasizing machine learning integration to enhance functionality. The application of machine learning methodologies improving biosignal processing, device adaptability, and diagnostic accuracy is discussed to introduce Machine Learning enhanced bioelectronics as a pathway toward ...
Myoungjae Oh, Enji Kim, Jakyoung Lee, Inhea Jeong, Eunmin Kim, Joonho Paek, Taekyeong Lee, Dayeon Kim, Seung Hyun An, Sumin Kim, Jung Ah Lim, Jang‐Ung Park   +11 more
wiley   +1 more source

Prediction of Myopia Among Undergraduate Students Using Ensemble Machine Learning Techniques. [PDF]

Health Sci Rep
Sifat IK, Jisa TA, Roy JS, Sultana N, Hasan F, Mosharaf MP, Kibria MK.   +6 more
europepmc   +1 more source

Non‐Invasive Diagnosis of Hypertrophic Cardiomyopathy by Breath

Advanced Sensor Research, EarlyView.
The use of sensor technologies for the diagnosis of hypertrophic cardiomyopathy (HCM) by identification of volatile organic compounds (VOCs) in breath samples. By combining gas chromatography‐mass spectrometry (GC‐MS) and electronic nose (eNose) platforms, specific VOC patterns associated with HCM are detected and analyzed.
Yael Hershkovitz‐Pollak, Manhal Habib, Yoav Y. Broza, Olga Katz, Harry Rakowski, Hossam Haick   +5 more
wiley   +1 more source

Predicting Transvaginal Surgical Mesh Exposure Outcomes Using an Integrated Dataset of Blood Cytokine Levels and Medical Record Data: Machine Learning Approach. [PDF]

JMIR Form Res
Waugh ML, Mills T, Boltin N, Wolf L, Parker P, Horner R, Wheeler Ii TL, Goodwin RL, Moss MA.   +8 more
europepmc   +1 more source

Machine Learning‐Driven Multi‐Objective Optimization of Microchannel Reactors for CO₂ Conversion

Advanced Sustainable Systems, EarlyView.
This study introduces a novel method that combines CFD, RSM, and ML to improve a microreactor's performance utilizing the Sabatier reaction. A range of ML models is assessed, and the best one is selected to predict optimal reactor conditions. ML shows the ability to predict performance in just milliseconds, leading to a decrease in computational time ...
Sandeep Kumar, Parmod Kumar, Kuljeet Singh Grewal   +2 more
wiley   +1 more source

Current status and trends of machine learning applied in clinical research of gastric cancer from 2004 to 2023: global bibliometric and visual analysis. [PDF]

Front Oncol
Wang X, Wu C, Yue S, Zhou M, Zhuo E, Wu X, Wang Y, Chen B, Wang F.   +8 more
europepmc   +1 more source

Hybrid geological modeling: Combining machine learning and multiple-point statistics

Computational Geosciences, 2020
T. Bai, P. Tahmasebi
semanticscholar   +1 more source

The Frequency‐Domain Lattice Boltzmann Method (FreqD‐LBM): A Versatile Tool to Predict the QCM Response Induced by Structured Samples

Advanced Theory and Simulations, EarlyView.
FreqD‐LBM simulates the oscillatory flow at the surface of a QCM‐D resonator in the presence of structured adsorbates. It derives shifts of frequency and bandwidth (equivalent to dissipation) on different overtones. Applications include rough surfaces, adsorbed rigid particles, adsorbed viscoelastic particles, spheres floating freely above the surface,
Diethelm Johannsmann, Paul Häusner, Arne Langhoff, Christian Leppin, Ilya Reviakine, Viktor Vanoppen   +5 more
wiley   +1 more source

SCARS-LOGISTIC: A novel variable selection approach for binary classification model to identify the significant determinants of sexually transmitted infections. [PDF]

PLoS One
Sadiq M, Alsadhan NA, Shah R, Younas S, Rasheed Z.   +4 more
europepmc   +1 more source