Results 121 to 130 of about 89,907 (213)

Outlier Detection in Mendelian Randomization. [PDF]

Stat Med
Mandl MM, Boulesteix AL, Burgess S, Zuber V.   +3 more
europepmc   +1 more source

Outlier Detection with Reinforcement Learning for Costly to Verify Data. [PDF]

Entropy (Basel), 2023
Nijhuis M, van Lelyveld I.
europepmc   +1 more source

Eutectic Gallium‐Indium as a Potential Non‐Toxic Replacement in Mercury Intrusion Porosimetry

Advanced Materials Technologies, EarlyView.
A practical alternative to mercury intrusion porosimetry is presented using non‐oxidized eutectic gallium‐indium. An eGaIn Filling Station enables oxygen‐free preparation of standard penetrometers, and the resulting measurements faithfully reproduce pore‐size distributions and intrusion volumes measured with mercury across several standard reference ...
Denis Schuetz, Michael F. Noisternig, Manuel Brandstaetter, Valentin Seyfried, Norbert Reitinger, Bernhard Nell, Alexander Kasper, Riaz Ahmad, Martin Thomas   +8 more
wiley   +1 more source

Outlier detection of skill decision differences of football penalty takers from a data-driven perspective: multialgorit hm modeling and empirical research of eye-tracking data. [PDF]

Front Sports Act Living
Li Z, Hu P, Liu H, Dai RC.
europepmc   +1 more source

Microscale 3D‐Printed Digital Strain Switches for Embedded Mechanical Computation

Advanced Materials Technologies, EarlyView.
Microscale 3D‐printed strain switches on flexible films convert deformation into native digital signals at geometry defined thresholds. A closed form model predicts switching from 3000 to 15 000 microstrain and is validated across 110 devices. Reliable ohmic closure and strain activated AND, OR, and XOR logic point toward low‐power mechanical ...
Regan Kubicek, Daniel Quinn, Gabriel Smith, Sarah Bergbreiter   +3 more
wiley   +1 more source

pyFLANK, a graph neural network based null distribution inference model for F_ST outlier detection. [PDF]

BMC Bioinformatics
Zhang Z, Jia W, Gomes Viana JP, Hsieh PH, Yoshikuni Y, Hudson M.   +5 more
europepmc   +1 more source

Structural Outlier Detection and Zernike-Canterakis Moments for Molecular Surface Meshes-Fast Implementation in Python. [PDF]

Molecules, 2023
Banach M.
europepmc   +1 more source

AI‐Powered Framework for Evaluating Drug Efficacy for Three‐Dimensional In Vitro Cancer Models in Robot‐Assisted Production

Advanced Robotics Research, EarlyView.
An AI‐powered, robot‐assisted framework automatically produces, images, and analyzes 3D tumor spheroids to evaluate drug efficacy. Integrated modules handle spheroid formation, live/dead staining, brightfield imaging, and automated image analysis, including spheroid segmentation, viability and metrics to assess the drug treatment efficacy. The workflow
Dalia Mahdy, Jesus Nieves, Lukas Königer, Matthias Peindl, Fabio Erhard, Marc Möllmann, Anke Klingner, Markus Münig, Bibin Babu, Thomas Schwarz, Marco Metzger, Gudrun Dandekar, Maximiliane Wußmann, Jan Hansmann   +13 more
wiley   +1 more source

Multiple outlier detection in samples with exponential & Pareto tails. [PDF]

J Appl Stat
Sornette D, Wei R.
europepmc   +1 more source

EnsMOD: A Software Program for Omics Sample Outlier Detection. [PDF]

J Comput Biol, 2023
Manes NP, Song J, Nita-Lazar A.
europepmc   +1 more source