Results 201 to 210 of about 495,754 (290)

Toward Environmentally Friendly Hydrogel‐Based Flexible Intelligent Sensor Systems

Advanced Intelligent Discovery, EarlyView.
This review summarizes environmentally and biologically friendly hydrogel‐based flexible sensor systems focusing on physical, chemical, and physiological sensors. Furthermore, device concepts moving forward for the practical application are discussed about wireless integration, the interface between hydrogel and dry electronics, automatic data analysis
Sudipta Kumar Sarkar, Kuniharu Takei
wiley   +1 more source

Proton Pump Inhibitors and Biomarkers of Haemostasis in Postmenopausal Women: The Buffalo OsteoPerio Study. [PDF]

Basic Clin Pharmacol Toxicol
Soliman AI, Wactawski-Wende J, Millen AE, Hovey KM, LaMonte MJ.   +4 more
europepmc   +1 more source

Machine Learning‐Assisted Infectious Disease Detection in Low‐Income Areas: Toward Rapid Triage of Dengue and Zika Virus Using Open‐Source Hardware

Advanced Intelligent Discovery, EarlyView.
This study introduces an affordable machine learning platform for simultaneous dengue and zika detection using fluorine‐doped tin oxide thin films modified with gold nanoparticles and DNA aptamers. Designed for low‐cost, hardware‐limited devices (< $25), the model achieves 95.3% accuracy and uses only 9.4 kB of RAM, demonstrating viability for resource‐
Marina Ribeiro Batistuti Sawazaki, Bassam Bachour Junior, Marcelo Mulato, José Ilton de Oliveira Filho   +3 more
wiley   +1 more source

Robust learning for ridge-penalized quasi-GLMs under non-identical distributions. [PDF]

Sci Rep
Zhang H, Tian W, Yao Q, Wang P, Zhang B.
europepmc   +1 more source

Artificial Intelligence‐Driven Insights into Electrospinning: Machine Learning Models to Predict Cotton‐Wool‐Like Structure of Electrospun Fibers

Advanced Intelligent Discovery, EarlyView.
Electrospinning allows the fabrication of fibrous 3D cotton‐wool‐like scaffolds for tissue engineering. Optimizing this process traditionally relies on trial‐and‐error approaches, and artificial intelligence (AI)‐based tools can support it, with the prediction of fiber properties. This work uses machine learning to classify and predict the structure of
Paolo D’Elia, Giovanna Pappalardo, Aldo R. Boccaccini, Liliana Liverani   +3 more
wiley   +1 more source

Extended Joinpoint Regression Methodology for Complex Survey Data. [PDF]

Stat Med
Liu B, Kim HJ, Zou J, Feuer EJ, Graubard BI.   +4 more
europepmc   +1 more source

Automation of Surgical Workflow Recognition: Unveiling the Surgical Instrument Kinematics that Underly Robot‐Assisted Prostatectomy Procedures

Advanced Intelligent Discovery, EarlyView.
Automated procedural analysis is recognized as one of the major game changers for robotic surgery. Meaning digital analysis needs to replace the manual assessments that set todays standard. Mechanical robotic‐instrument tracking enables the derivation of quantitative kinematic metrics that support behavior‐based workflow segmentation into distinct ...
Kateryna Pirkovets, Matthias N. van Oosterom, Vera A. Ottens, Henk G. van der Poel, Fijs W. B. van Leeuwen   +4 more
wiley   +1 more source

A statistical inference framework for FSNBLR: Modeling underdeveloped regional status in Eastern Indonesia. [PDF]

MethodsX
Zulfadhli M, Budiantara IN, Ratnasari V, Saffa Suriaslan A, Chandra Dhewy R.   +4 more
europepmc   +1 more source

Screw‐Based Pill for Intelligent Robotic Extraction of Viscous Fluids in Medical Applications

Advanced Intelligent Systems, EarlyView.
Screw‐based pill for intelligent robotic extraction (S‐PIRE) is a magnetically actuated smart capsule with a motorized screw, 3‐axis sensor, and Bluetooth control for site‐specific and minimally invasive remote sampling of viscous fluids, overcoming passive diffusion limitations.
Prima Dewi Sinawang, Victor Garcia‐Gradilla, Fernando Soto, Demir Akin, Margaret Braunreuther, Gerald G. Fuller, Utkan Demirci   +6 more
wiley   +1 more source

Collaborative Inference for Accelerated Failure Time Model Using Clinical Center-Level Summary Statistics. [PDF]

Stat Med
Hu M, Shi X, Gong Z, Song PX.
europepmc   +1 more source