Results 211 to 220 of about 17,286,028 (305)

Predicting autism spectrum disorder severity in children based on specific language milestones: a random forest model approach. [PDF]

Child Adolesc Psychiatry Ment Health
Xiong H, Xiang X, Liu X, Yang T, Chen J, Chen J, Li T.   +6 more
europepmc   +1 more source

Multitask Deep Learning Model for Predicting Lymph Node Metastasis and Disease‐Free Survival From Cytology Images in Bladder Cancer: A Multicenter Study With Pan‐Cytology Validation

Advanced Science, EarlyView.
Through self‐supervised pretraining and supervised fine‐tuning on large‐scale cytology image datasets, CytoNet predicts lymph node metastasis and survival. Across independent cohorts, this multitask framework demonstrates robust performance, improves risk stratification beyond radiological assessment, and provides interpretable evidence to support ...
Guibin Hong, Fan Jiang, Ye Xie, Xiaowei Huang, Runnan Shen, Yun Wang, Mengyi Zhu, Haoxuan Wang, Hongkun Yang, Yanxiao Nie, Zhen Lin, Rui Chen, Nengtai Ouyang, Tianxin Lin, Shaoxu Wu   +14 more
wiley   +1 more source

Hierarchical random forest model, inflammation and oxidative stress as predictors of the atherogenic index of plasma and diabetes progression. [PDF]

Sci Rep
Jelinek HF, Muteir I, Al-Aubaidy H.
europepmc   +1 more source

A Global Methane Observation System to Reduce Uncertainty for Anthropogenic and Natural Sources and Sinks for Detecting and Attributing Climate Feedbacks

Advanced Science, EarlyView.
Conceptual illustration of a Global Ecosystem Methane Observing System (GEM‐OS) integrating satellites, aircraft, atmospheric networks, and ecosystem measurements to quantify methane emissions from anthropogenic and natural sources. The multi‐scale observing framework improves source attribution, reduces uncertainty in regional methane budgets, and ...
P. Ciais, S. Peng, J. Chang, F. Li, Q. Zhu, K. Yuan, G. Hugelius, H. Li, Y. Cai, F. Chevallier, K. Tibrewal, E. A. Kort, K. Arndt, J. Watts, B. Buma, N. Besic, P. I. Palmer, H. Cadillo‐Quiroz, E. Euskirchen, M. J. Gondwe, A. Hoyt, R. Jackson, S. Malone, D. Monteverde, S. Natali, M. Ramonet, C. Rey‐Sanchez, L. B. Sagang, E. A. G. Schuur, R. Vargas, R. Varner, Z. Zhang, B. Poulter   +32 more
wiley   +1 more source

Prediction of loess collapsibility coefficient using bayesian optimized random forest model. [PDF]

Sci Rep
Zhang W, Guo J, Li Z, Cheng R, Ning C, Niu H, Liu Z.   +6 more
europepmc   +1 more source

Artificial Intelligence‐Guided Phenotypic Drug Repurposing Against Streptococcus pneumoniae

Advanced Science, EarlyView.
Integrated artificial intelligence (AI) ensembles identify highly potent repurposed drugs against Streptococcus pneumoniae. Prospective virtual screening of 6747 drugs uncovers nine active candidates, including thiostrepton. This drug exhibits low picomolar potency and bypasses established resistance in multidrug‐resistant strains, demonstrating an ...
Joshua S. Fitch, Muhammad D. Ariadi, Min Jung Kwun, Leonie Howells, Saiveth Hernandez‐Hernandez, Nicholas J. Croucher, Pedro J. Ballester   +6 more
wiley   +1 more source

Biochemically Constrained Multi‐Omics Integration Reveals Protein–Metabolite Dependencies Across Diseases

Advanced Science, EarlyView.
ProMetNet introduces a biologically constrained deep learning framework for proteo‐metabolomic integration by embedding Reactome‐derived pathway topology into neural networks. It captures non‐linear molecular dependencies and pathway‐level metabolic reorganization, enabling interpretable discrimination.
Minghui Zhao, Na Zhou, Ruotong Liu, Xiaofei Li, Jian Li, Fuzhong Xue, Qingzhen Hou   +6 more
wiley   +1 more source

A nomogram and random forest model for predicting liver metastasis in patients with early-onset colorectal cancer. [PDF]

Sci Rep
Han X, Bai X, Zhang Q, Qian X.
europepmc   +1 more source

Neuromorphic Optical Tracking and Imaging of Randomly Moving Targets Through Dynamic Dense Scattering Media

Advanced Science, EarlyView.
Vision begins not with images but with change: the retina fires only when something moves, handing the brain a stream of spikes. A neuromorphic imaging system adopts the same strategy—an event sensor that sees like the retina, a spiking network that thinks like the brain—to track and reconstruct fully randomly moving targets through tissue (phantom ...
Ning Zhang, Arto Nurmikko
wiley   +1 more source

Exploring determinants of fear of cancer recurrence in postoperative colorectal cancer patients: a random forest model approach. [PDF]

J Cancer Res Clin Oncol
Wu J, Cao Y, Yao L, Chen L, Xu L.
europepmc   +1 more source