Results 261 to 270 of about 151,967 (341)

Separating predictive accuracy from functional behaviour in machine-learning surrogate models for geoengineering applications. [PDF]

Sci Rep
Żeruń M.
europepmc   +1 more source

Robots and Minimal, Physics‐Informed Features: A Hybrid Framework for Enzyme Catalysis

Advanced Science, EarlyView.
Robotic experimentation and physics‐informed machine learning combine to predict enzyme substrate scope. With a handful of interpretable features derived from docking and quantum mechanics calculations, our model rivals descriptor‐heavy AI approaches and extrapolates to unseen substrates and enzyme classes.
Natalia Onishchenko, Eric S. Larsen, Govind Paneru, Kisung Lee, Diana V. Kolygina, Yankai Jia, Elizabeth Maria Clarissa, Wai‐Shing Wong, Bartosz A. Grzybowski   +8 more
wiley   +1 more source

Non-Invasive Voice-Based Early Detection of Parkinson's Disease via Spectral Feature Analysis and Machine Learning Techniques. [PDF]

Bioengineering (Basel)
Varela-Arellano YO, Soto-Murillo MA, Alcalá-Ramírez V, Villagrana-Bañuelos KE, Salas-Rodriguez LR, Cepeda-Argüelles A, Villagrana-Bañuelos R, Galván-Tejada JI, Arceo-Olague JG, Galván-Tejada CE.   +9 more
europepmc   +1 more source

A Dual‐Mode In Situ EV‐miRNA Profiling Platform for Machine‐Learning‐Assisted Gastric Cancer Liquid Biopsy

Advanced Science, EarlyView.
An in situ dual‐mode platform integrates fusogenic liposomes with localized autocatalytic DNA circuits for plasma‐derived extracellular vesicle microRNA analysis. Following membrane fusion, target miRNAs trigger feedback‐assisted LECHA amplification inside intact vesicles, generating fluorescence and electrochemical outputs. Machine learning integrates
Wenbin Li, Rui Fan, Kun Xie, Jiehua Zhong, Yitong Zhu, Tingting Ji, Yuanyuan Qin, Shijin Peng, Yu Zhang, Yuhang Guo, Tiange Zhang, Chunchen Liu, Bo Li, Lei Zheng, Ye Zhang, Xiaohui Yan   +15 more
wiley   +1 more source

A framework for estimating cardiorespiratory fitness from diverse exercise tests. [PDF]

Npj Exerc Med Health
Gonzales TI, Wareham N, Brage S.
europepmc   +1 more source

Similarity‐Enhanced Representation Learning of Non‐Canonical Amino Acids for Therapeutic Peptide Modeling

Advanced Science, EarlyView.
Non‐canonical amino acids (ncAAs) enhance peptide therapeutics but remain difficult to model computationally. SinCAA, a similarity‐enhanced pretraining framework, jointly optimizes contrastive learning guided by a novel conformational similarity metric with masked node reconstruction, capturing both functional relationships and chemical identity of ...
Chencheng Xu, Lesong Wei, Jianmin Wang, Yuanpeng Xiong, Ruochi Zhang, Yu Wang, Chao Zha, Qiangcheng Zeng, Xin Gao   +8 more
wiley   +1 more source

Performance trade-offs between dense prediction and sparse query mechanisms for brain tumor MRI detection: a comparative study of YOLOv8 and RT-DETR. [PDF]

Front Med (Lausanne)
Xie L, Chen J, Sun Z, Huang Y, Ye S, Ye C.   +5 more
europepmc   +1 more source

AI‐Powered, Temperature‐Resolved Centrifugal Microfluidics for Rapid 3D Phase‐Diagram Generation of Biomolecular Condensates

Advanced Science, EarlyView.
By merging centrifugal microfluidics, precise temperature control, and AI image recognition, T‐PhaseMap transforms biomolecular condensate phase mapping into a rapid, temperature‐resolved workflow. It generates 3D composition–temperature phase diagrams within 30 min, resolves four phase states, and uncovers temperature‐dependent heparin sodium ...
Jiashuo Li, Pengjie Li, Kaiting Zhang, Yongqi Guo, Peng Chen, Bi‐Feng Liu, Yiwei Li   +6 more
wiley   +1 more source

A novel deep learning prediction method for PM2.5 integrating improved MSTL decomposition and FATA optimization algorithm. [PDF]

PLoS One
Zhao X, Qiao P, Bharti B, Li H, Yang S, Shi Q, Qin Q, Chen J.   +7 more
europepmc   +1 more source

MethyAnno: An Interpretable Automated Annotation Method Leveraging Multi‐Scale Information and Metric Learning Framework for scDNAm Data

Advanced Science, EarlyView.
MethyAnno enables robust and interpretable annotation of single‐cell DNA methylation data by integrating multi‐scale epigenetic information, bidirectional cross‐attention, and prototype‐based metric learning. The framework resolves rare and novel cell types across datasets while revealing cell‐type‐specific epigenetic signatures associated with disease
Yuhang Jia, Siyu Li, Songming Tang, Keju Gu, Shengquan Chen   +4 more
wiley   +1 more source