Results 231 to 240 of about 156,766 (287)

Overcoming the Nyquist Limit in Molecular Hyperspectral Imaging by Reinforcement Learning

Advanced Intelligent Discovery, EarlyView.
Explorative spectral acquisition guide automatically selects informative spectral bands to optimize downstream tasks, outperforming full‐spectrum acquisition. The selected hyperspectral data are used for tasks such as unmixing and segmentation. BandOptiNet encodes selection states and outputs optimal bands to guide spectral acquisition. Recent advances
Xiaobin Tang, Yongqing Zhang, Xinyu Deng, Hyeon Jeong Lee, Delong Zhang   +4 more
wiley   +1 more source

Skill-File-Guided Virtual Screening: A Single-Target Formyl Peptide Receptor 2 Case Study of Large-Language-Model-Coordinated Physics and Diffusion Docking. [PDF]

Comput Struct Biotechnol J
Gani O.
europepmc   +1 more source

Automated Bacterial Identification and Morphological Feature Analysis in Low‐Dose Cryo‐EM Using YOLOv11

Advanced Intelligent Discovery, EarlyView.
AI‐based tools enable rapid characterization of bacterial ultrastructure in low‐dose cryogenic transmission electron microscopy. The envelope thickness tool quantifies membrane thickness and anisotropy. The flagella module analyzes filament morphology and detects cell‐flagella contacts.
Sita Sirisha Madugula, Lynnicia N. Massenburg, Spenser R. Brown, Amber N. Bible, Chanda R. Harris, Lance X. Zhang, Kiara Parker, Scott T. Retterer, Jennifer L. Morrell‐Falvey, Rama K. Vasudevan, Alexis N. Williams   +10 more
wiley   +1 more source

Deploying YOLO for whole-slide mitosis detection: A transparent, auditable, and reproducible pipeline for pathology AI-assisted diagnosis and decision-support tool. [PDF]

J Pathol Inform
Obami PO, Ketkar A, Fasogbon SA, Odega K, Udo IA, Ajani OF, Osuji BM, Moronkeji A, Adegboye AA, Omisakin IA.   +9 more
europepmc   +1 more source

AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective

Advanced Intelligent Discovery, EarlyView.
The exponential growth of cancer multi‐omics data brings opportunities and challenges for precision oncology. This review systematically examines AI's role in addressing these challenges, covering generative models, integration architectures, Explainable AI for clinical trust, clinical applications, and key directions for clinical translation.
Shilong Liu, Shunxiang Li, Kun Qian
wiley   +1 more source

Biologically informed neural network models are robust to spurious interactions via self-pruning. [PDF]

Bioinformatics
Nordenstorm O, Baghdassarian H, Xu X, Lauffenburger DA, Nilsson A.   +4 more
europepmc   +1 more source

An Ultrafast GPU-Enabled MGVB. [PDF]

Proteomes
Metodiev MV.
europepmc   +1 more source

Characterization of high-resolution AI data center training workloads on single and multiple GPU nodes. [PDF]

Sci Data
Elsayed AAE, Al-Obaidi AA, Farag HEZ.
europepmc   +1 more source

NeutronJittor: Efficient CPU-GPU memory management for GNN training with Jittor. [PDF]

Fundam Res
Lu S, Fu Z, Wang Q, Zhang Y, Xu Y, Ai X, Wei Z, Yu G.   +7 more
europepmc   +1 more source

GPU-Accelerated Signal Processing for Distributed Vibration Sensing Based on OVNA Method. [PDF]

Sensors (Basel)
Meoli A, Vallifuoco R, Coscetta A, Zeni L, Minardo A.   +4 more
europepmc   +1 more source