Results 161 to 170 of about 414,528 (301)

Application of unsupervised learning to cluster swine breeding herds based on key performance indicators in Southern Brazil. [PDF]

Transl Anim Sci
Ulguim RR, Pereira MA, Tavares J, Linhares DCL, Mellagi APG, Bortolozzo FP, Tecchio CA, Nagae RY, Cavazini NC, de Lara AC, Silva GS.   +10 more
europepmc   +1 more source

Machine Learning‐Driven Digital Twin of a Field‐Effect Transistor‐Based Hormone Biosensor for Real‐Time Estradiol Monitoring

Advanced Intelligent Systems, EarlyView.
A machine learning‐driven digital twin simulates an aptamer‐functionalized BioFET measuring 17β‐estradiol. Real‐time Isd signals are processed, features are extracted, and trained models estimate hormone concentration. In parallel, a one‐step‐ahead forward model learns biosensor dynamics and generates realistic synthetic signals, enabling in silico ...
Anastasiia Gorelova, Alexandra Parichenko, Shirong Huang, Santiago Melia, Gianaurelio Cuniberti   +4 more
wiley   +1 more source

Uncovering Hidden Prognostic Patterns in Colorectal Cancer Histology Using Unsupervised Learning: A Computational Pathology Study. [PDF]

Bioengineering (Basel)
Zhou WT, Liu Y, Yu G, Wang KS, Xu C, Greenbaum J, Wu C, Jiang LD, Papasian CJ, Xiao HM, Deng HW.   +10 more
europepmc   +1 more source

Data-Driven Calibration of Large Liquid Detectors with Unsupervised Learning

Scott DeGraw, S. D. Biller, Armin Reichold   +2 more
openalex   +1 more source

Integrating Artificial Intelligence With Droplet‐Based Microfluidics: Advances, Challenges, and Emerging Opportunities

Advanced Intelligent Systems, EarlyView.
Droplet‐based microfluidics enables precise, high‐throughput microscale reactions but continues to face challenges in scalability, reproducibility, and data complexity. This review examines how artificial intelligence enhances droplet generation, detection, sorting, and adaptive control and discusses emerging opportunities for clinical and industrial ...
Junyan Lai, Sukrit Gaira, Rongfeng Wang, Qingtian Zhang, Ming Li, Liao Wu, Diangeng Li, Yi Li, Chengchen Zhang, Jinhong Guo, Shi‐Yang Tang   +10 more
wiley   +1 more source

Early damage detection in bridges using a variational autoencoder-based hybrid unsupervised learning framework. [PDF]

Sci Rep
Pakzad SS, Masoodi AR.
europepmc   +1 more source

ADVANCEMENTS IN SENTIMENT ANALYSIS: A DETAILED EXPLORATION OF SUPERVISED AND UNSUPERVISED LEARNING APPROACHES

S. Angeline Yuvancy, M. Elavarashi, PS. Razy   +2 more
openalex   +1 more source

On The Philosophy of Unsupervised Learning

, 2022
David Watson
openalex   +1 more source

Terrestrial Cyborg Insects for Real‐Life Applications

Advanced Intelligent Systems, EarlyView.
This article reviews the development of terrestrial cyborg insects from their emergence in 1997 to mid‐2025, examining three key aspects: locomotion control methods, associated challenges with proposed solutions, and practical applications. Framing these biohybrid systems as insect‐scale mobile robots, the review provides foundational insights for new ...
Hai Nhan Le, Lachlan Fitzgerald, Phuoc Thien Phan, Robbie Wilson, Christofer Clemente, Huu Duoc Nguyen, Hirotaka Sato, Hoang‐Phuong Phan, Peter Ross McAree, Thanh Nho Do, Tat Thang Vo‐Doan   +10 more
wiley   +1 more source

Leveraging productivity indicators for anomaly detection in swine breeding herds with unsupervised learning. [PDF]

Front Vet Sci
Pedro Mil-Homens M, Wang C, Trevisan G, Dórea F, Linhares DCL, Holtkamp D, Silva GS.   +6 more
europepmc   +1 more source