Results 131 to 140 of about 63,062 (305)

A Robust Deep Temporal Causal Discovery Platform for Single‐Cell Gene Regulatory Network Reconstruction

Advanced Intelligent Discovery, EarlyView.
scTIGER2.0 is a deep‐learning framework that infers gene regulatory networks from single‐cell RNA sequencing data. By integrating correlation, pseudotime ordering, deep learning and bootstrap‐based significance testing, it reduces false positives and reveals directional gene interactions.
Nishi Gupta, Madison Dautle, Shaoqiang Zhang, Yong Chen   +3 more
wiley   +1 more source

Large‐Scale Machine Learning to Screen for Small‐Molecule Senolytics

Advanced Intelligent Discovery, EarlyView.
A consistent workflow underpins all experiments in this study. A dedicated model‐selection dataset first identifies optimal hyperparameters for each algorithm. Models are then trained and rigorously evaluated on independent sets of molecules using the senolytic ratio SR. Comprehensive hyperparameter exploration across SMILES representations, task types,
Alexis Dougha, Jesus Gil, Pedro J. Ballester   +2 more
wiley   +1 more source

Acceptability of the text messaging intervention.

, 2019
Acceptability of the text messaging intervention.
Eyitayo Omolara Owolabi (8053025), Anthony Idowu Ajayi (4389463), Daniel Ter Goon (8053028)   +2 more
core   +1 more source

Population-Based Digital Health Interventions to Deliver at-Home COVID-19 Testing: SCALE-UP II Randomized Clinical Trial

Journal of Medical Internet Research
BackgroundDigital health interventions could be a scalable approach to delivering at-home COVID-19 testing. ObjectiveSCALE-UP II aimed to investigate the effectiveness of 3 digital health interventions on the delivery of mailed at-home COVID ...
Guilherme Del Fiol, Tatyana V Kuzmenko, Brian Orleans, Jonathan J Chipman, Tom Greene, Ray Meads, Kimberly A Kaphingst, Bryan Gibson, Kensaku Kawamoto, Andy J King, Tracey Siaperas, Shlisa Hughes, Alan Pruhs, Courtney Pariera Dinkins, Cho Y Lam, Joni H Pierce, Ryzen Benson, Emerson P Borsato, Ryan C Cornia, Leticia Stevens, Richard L Bradshaw, Chelsey R Schlechter, David W Wetter   +22 more
doaj   +1 more source

Text Message from the Congo [PDF]

The American Journal of Tropical Medicine and Hygiene, 2021
openaire   +2 more sources

Artificial Intelligence‐Driven Network Pharmacology: A Methodological Paradigm Shift Bridging Traditional Wisdom and Modern Science

Advanced Intelligent Discovery, EarlyView.
Artificial intelligence is redefining network pharmacology (NP). By integrating knowledge graph engineering, geometric deep learning, multiomics anchoring, and generative reasoning, AI‐driven NP (AI‐NP) transforms static target mapping into dynamic, predictive modeling.
Cong Wang, Sile Hu, Rigahai Ji, Riguna A, Siqige Hao, Ma Zhuo, Yi‐Hung Chen, Bisihalatu Hu, Ulana Bai, Xigui Hada   +9 more
wiley   +1 more source

Probing Machine Learning Interatomic Potentials on Ion Transport Properties

Advanced Intelligent Discovery, EarlyView.
We perform a systematic benchmark of six state‐of‐the‐art universal machine learning interatomic potentials on their ability to predict ion transport properties in lithium‐ and sodium‐based superionic conductors relevant to all‐solid‐state batteries.
Ogheneyoma Aghoghovbia, Ming Hu, Adji Bousso Dieng   +2 more
wiley   +1 more source

Synchronous Text Messaging [PDF]

, 2017
We have created and evaluated a novel mobile messaging app named Curtains Messenger. The app has been designed to support synchrony in messaging. It does this by requiring users to be in the app at the same time as each other in order to send, receive and read messages.
Podlubny, Martin, Rooksby, John, Rost, Mattias, Chalmers, Matthew   +3 more
openaire  

Lidar‐Based Object Tracking of Traffic Participants with Sensor Nodes in Existing Urban Infrastructure

Advanced Intelligent Systems, EarlyView.
This paper presents a lidar‐based sensor node design and a rule‐based state observer for edge‐based traffic participant tracking. Unlike other state‐of‐the‐art methods, this state observer enables real‐time, CPU‐only edge processing without relying on machine learning approaches.
Simon Schäfer, Bassam Alrifaee, Ehsan Hashemi   +2 more
wiley   +1 more source

The Effects Of Text Messaging On Driver Distraction: A Bio-Behavioral Analysis

, 2010
This study was designed to empirically examine the effects of text-messaging on driver distraction. Thirty participants were required to perform a driving simulation task while text- messaging using a cellular phone device.
Brill, J. Christopher, Mouloua, Mustapha, Rinalducci, Edward, Alberti, Pascal, Ahern, Amber   +4 more
core   +1 more source