Results 151 to 160 of about 128,875 (283)

PEPbench-Open, Reproducible, and Systematic Benchmarking of Automated Pre-Ejection Period Extraction Algorithms. [PDF]

Psychophysiology
Richer R, Jorkowitz J, Stühler S, Abel L, Kurz M, Oesten M, Griesshammer SG, Albrecht NC, Küderle A, Ostgathe C, Kölpin A, Steigleder T, Rohleder N, Eskofier BM.   +13 more
europepmc   +1 more source

Multivariate Contrastive Predictive Coding with Sliding Windows for Disease Prediction from Electronic Health Records

Advanced Intelligent Systems, EarlyView.
Adaptive multi‐indicator contrastive predictive coding is introduced as a self‐supervised pretraining framework for multivariate EHR time series. An adaptive sliding‐window algorithm and 2D convolutional neural network encoder capture localized temporal patterns and global indicator dependencies, enabling label‐efficient disease prediction that ...
Hongxu Yuan, Xiaozhu Jing, Yuzheng Yan, Wuman Luo   +3 more
wiley   +1 more source

The Role of MER Processing Pipelines for STN Functional Identification During DBS Surgery: A Feature-Based Machine Learning Approach. [PDF]

Bioengineering (Basel)
Levi V, Coelli S, Gorlini C, Forzanini F, Rinaldo S, Golfrè Andreasi N, Romito L, Eleopra R, Bianchi AM.   +8 more
europepmc   +1 more source

Autonomous Robotic Colonoscopy: A Supervised Learning Approach for Enhanced Navigation and Collision Detection

Advanced Intelligent Systems, EarlyView.
A novel autonomous robotic colonoscopy is introduced through supervised learning approaches. The proposed system consists of 3 degrees of freedom motorized colonoscope with an integrated navigation module that can infer a target steering point and collision probability.
Bohyun Hwang, Dae Kyung Sohn, Seonggun Joe, Byungkyu Kim   +3 more
wiley   +1 more source

‌Rockburst intensity grading prediction based on the LOF-ENN-KNN model‌. [PDF]

Sci Rep
Ge H, Zhang J, Ma C, Hui K, Li Y, Wu Z.
europepmc   +1 more source

RanBALL: An Ensemble Machine Learning Framework for Accurate Subtype Identification of Pediatric B‐Cell Acute Lymphoblastic Leukemia

Advanced Intelligent Systems, EarlyView.
Here, we present RanBALL, an ensemble random projection‐based model for accurate and cost‐effective identification of B‐cell acute lymphoblastic leukemia subtypes is presented. By preserving patient‐to‐patient distance after dimension reduction by random projection and ensemble learning, RanBALL can facilitate the discovery of B‐ALL subtype‐specific ...
Lusheng Li, Hanyu Xiao, Xinchao Wu, Zhenya Tang, Joseph D. Khoury, Jieqiong Wang, Shibiao Wan   +6 more
wiley   +1 more source

A new hybrid model for improving outlier detection using combined autoencoder and variational autoencoder. [PDF]

Sci Rep
Daoud AM, Elkomy OM, Khedr WI, Hosny KM.
europepmc   +1 more source

GraphNeuralCloth: A Graph‐Neural‐Network‐Based Framework for Non‐Skinning Cloth Simulation

Advanced Intelligent Systems, EarlyView.
This study presents a cloth motion capture system and a point‐cloud‐to‐mesh processing method to support the prediction of real‐world fabric deformation. GraphNeuralCloth, a graph neural‐network (GNN)‐based framework is also proposed to estimate the cloth morphology change in real time.
Yingqi Li, Xiaomei Wang, Xiaoqi Song, Chenchen Fan, Bohao Zhu, Jianan Peng, Qixin Liang, James Lam, Kam‐Yim Sze, Ka‐Wai Kwok   +9 more
wiley   +1 more source

PCA‐Based Database Mining Enables the Discovery of Bacterial Carbene Transferases for Stereodivergent Cyclopropanation

Angewandte Chemie, EarlyView.
Database mining using principal component analysis (PCA)‐based clustering enabled discovery of bacterial enzymes capable of catalyzing stereodivergent cyclopropanation of styrene. Statistical analyses of sequence data further revealed characteristic structural properties of these enzymes, highlighting the potential of the bioinformatics tools for ...
Shunsuke Kato, Koki Takeuchi, Kohei Umeda, Hisashi Kudo, Tomohisa Hasunuma, Takashi Hayashi   +5 more
wiley   +2 more sources

Development of Hourly Resolution Air Temperature Across Titicaca Lake on Auxiliary ERA5 Variables and Machine Learning-Based Gap-Filling. [PDF]

Sensors (Basel)
Sirpa-Poma JW, Calle J, Uscamayta-Ferrano E, Molina-Carpio J, Satgé F, Cuentas Toledo O, Duran R, Pacheco Mollinedo P, Hussain R, Pillco-Zolá R.   +9 more
europepmc   +1 more source