Results 241 to 250 of about 549,786 (309)
Self-supervised deep learning for advancing macromolecular analysis in cryo-electron tomography
Stojanovska, Frosina
openalex +1 more source
Understanding protein sequence–function relationships remains challenging due to poorly defined motifs and limited residue‐level annotations. An annotation‐agnostic framework is introduced that segments protein sequences into “protein words” using attention patterns from protein language models.
Hedi Chen +9 more
wiley +1 more source
Multimodal Self-Supervised Learning for Early Alzheimer's: Cross-Modal MRI-PET, Longitudinal Signals, and Site Invariance. [PDF]
Ali SB +3 more
europepmc +1 more source
Anomaly classification based on self-supervised learning and its application
Yongsheng Han, Zhiquan Qi, Yingjie Tian
openalex +1 more source
A Lattice Genome framework links geometric and process “genes” to lattice “phenotypes” via correction‐calibrated high‐throughput simulations and a growing performance database. Genome‐driven retrieval and recombination of unit cells enables component‐level, regionally tailored multi‐objective design: stress fields are programmed under constant relative
Haoyuan Deng +8 more
wiley +1 more source
Data-Efficient Deep Learning Framework for Urolithiasis Detection Using Transfer and Self-Supervised Learning. [PDF]
Kim JS, Eun SJ.
europepmc +1 more source
This manuscript presents the WDMS platform, an AI‐assisted, self‐powered wearable dual‐mode sensor for tele‐neurology. It integrates a contact–separation TENG insole with stretchable polyurethane optical‐fiber strain sensors to synchronously track plantar pressure and lower‐limb muscle deformation.
Tianliang Li +12 more
wiley +1 more source
Self-supervised learning with BYOL for anterior cruciate ligament tear detection from knee MRI. [PDF]
Aidarkhan A +7 more
europepmc +1 more source
Smart Optogenetics for Real‐Time Automated Control of Cardiac Electrical Activity
We are able to stop dangerous heart‐rhythm spirals before they fully form. Within about 100 ms, it pinpoints the spiral's tiny central tip (≈0.9 mm) using light‐based sensing and machine learning, then shines targeted light to shut it down. This fast, precise, closed‐loop approach detects, targets, and terminates arrhythmias in real time.
Shanliang Deng +15 more
wiley +1 more source
DINO-EYE: self-supervised learning for identification of different optic disc phenotypes in primary open angle glaucoma. [PDF]
Grassi L, Fei Z, Morales E, Caprioli J.
europepmc +1 more source

