Results 201 to 210 of about 94,020 (294)

Cellpose+, a Morphological Analysis Tool for Feature Extraction of Stained Cell Images

open access: yesAdvanced Intelligent Discovery, EarlyView.
We introduce Cellpose plus, a morphological and geometrical analysis tool for feature extraction of stained cell images built over Cellpose, a state‐of‐the‐art cell segmentation framework. We also introduce a dataset of DAPI and FITC stained cells to which our new method is applied.
Israel A. Huaman   +10 more
wiley   +1 more source

Medical education in Obstetrics and Gynecology: preferences of medical students regarding digital teaching. [PDF]

open access: yesFront Med (Lausanne)
Cirkel C   +5 more
europepmc   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

open access: yesAdvanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

RetINaBox: A Hands-On Learning Tool for Experimental Neuroscience. [PDF]

open access: yeseNeuro
Bettler B   +9 more
europepmc   +1 more source

Collaborative Online International Learning With Prelicensure Nursing Students: Teaching Family-Centered Care Through a Global Perspective

open access: hybrid
Beth Cosgrove   +6 more
openalex   +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

open access: yesAdvanced 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   +3 more
wiley   +1 more source

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

open access: yesAdvanced 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   +3 more
wiley   +1 more source

Autonomous Machine Learning‐Based Classification and Arrangement of Submillimeter Objects Using a Capillary Force Gripper

open access: yesAdvanced Intelligent Discovery, EarlyView.
This study presents an automated system integrating a capillary force gripper and machine learning‐based object detection for sorting and placing submillimeter objects. The system achieved stable and simultaneous manipulation of four object types, with an average task time of 86.0 seconds and a positioning error of 157 ± 84 µm, highlighting its ...
Satoshi Ando   +4 more
wiley   +1 more source

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