Results 181 to 190 of about 40,989 (265)

How Advanced Artificial Intelligence Technologies Shape Drug–Drug and Drug–Target Interaction Modeling

Advanced Science, EarlyView.
This review explores the convergence of artificial intelligence technologies in modeling drug–drug and drug–target interactions. By evaluating advanced feature engineering, architectural innovations, and learning paradigms reveals shared evolutionary trends and critical challenges, such as cold‐start settings and shortcut learning.
Xin Sun, Tong Wang
wiley   +1 more source

Enhanced classification approach using MI-SVM for imbalanced multi-class datasets. [PDF]

Sci Rep
Patel V, Bhavsar H.
europepmc   +1 more source

A Non‐Canonical Role of SMAD4 in Regulating 3D Genome Architecture to Inhibit Lung Squamous Cell Carcinoma Development

Advanced Science, EarlyView.
SMAD4 is identified as a guardian of 3D genome architecture in lung squamous cell carcinoma. Loss of SMAD4 unleashes EP300 at chromatin loop anchors, strengthening enhancer–promoter looping and H3K27ac at the SOX2 locus to drive aberrant SOX2 activation and tumor cell proliferation.
Qian Tang, Chen Lian, Xinyan Han, Xuhan Zhang, Zihan Wang, Boyu Wang, Taoyu Zhu, Xinrui Lin, Xiaolei Wang, Yaping Xu, Manyu Xiao, Zijin Wang, Junming Li, Silin Chen, Yunze Wang, Yufei Liu, Songsong Li, Zuolin Shen, Xi Lu, Xueqi Han, Yilu Zhou, Mingyang Xiao, Jiayi Ran, Xiaoran Cao, Xinyi Xu, Hugo Sámano‐Sánchez, Alfredo Rodríguez, Lian Wang, Shuifang Chen, Zhanyu Xu, Shirong Zhang, Nuo Yang, Yong Tang, Jian Liu   +33 more
wiley   +1 more source

Artificial Intelligence‐Based Body Composition Analysis Reveals Sex‐Specific Prognostic Markers and Their Clinical Value in Gastric Cancer: A Multicenter Study

Advanced Science, EarlyView.
This study applied AI to quantify multidimensional body composition from CT images in gastric cancer and healthy controls. Distinct sex‐specific patterns and disease‐related alterations were identified and were associated with survival. Higher muscle and fat measures were linked to improved outcomes.
Tianxiang Li, Tingting Liu, Qian Yang, Zhiqing Zhang, Xiaofang Guo, Xiang Wang, Yihan Zhang, Limin Ge, Yu Su, Wenjun Wu, Weihua Guo, Zheng Wang, Lian Yang, Yanfeng Niu   +13 more
wiley   +1 more source

Marketing analytics in banking 4.0: A two-stage explainable AI framework for high-accuracy and well-calibrated predictions. [PDF]

PLoS One
Nasir F, Ali Ahmed A, Yevseyeva I, Kiraz MS.   +3 more
europepmc   +1 more source

The precision-recall plot is more informative than the ROC plot when evaluating binary classifiers on imbalanced datasets. [PDF]

PLoS One, 2015
Saito T, Rehmsmeier M.
europepmc   +1 more source

Histone Modification Complex JMJ704‐HDA709 Negatively Regulates Salinity Tolerance in Rice

Advanced Science, EarlyView.
This study reveals that the rice histone demethylase JMJ704 interacts with HDA709―a H3K9ac deacetylase characterized herein―to form a chromatin‐modifying complex. Under salt stress, OsWRKY72 recruits this complex through interaction with JMJ704 to target loci, repressing the expression of oxidative stress and salt‐responsive genes via removal of ...
Jing Wang, Zhengting Chen, Pengxiang Bai, Biao Liu, Lingling Meng, Jian Zhang, Xu Li, Dao‐Xiu Zhou, Xuan Ma, Yu Zhao   +9 more
wiley   +1 more source

Step-Wise Dual Dynamic DPSGD: Enhancing Performance on Imbalanced Medical Datasets with Differential Privacy. [PDF]

Entropy (Basel)
Huang X, Xie F.
europepmc   +1 more source

A Sprayable Nanoplatform Breaks the Vicious Cycle of Diabetic Wounds via Photoactivated Antioxidant and Drug Delivery

Advanced Science, EarlyView.
A sprayable near‐infrared‐activated nanoplatform incorporating MXene, ZnHCF nanozyme, and deferoxamine efficiently breaks the vicious cycle of diabetic wounds. Upon irradiation, interfacial electron transfer and photothermal effects enhance multi‐enzyme activity, enabling explosive ROS elimination, alleviation of hypoxia, and controlled DFO release ...
Jiahao Guo, Yuanyuan Meng, Qixiang Gui, Xi‐Tao Yang, Yong Fan, Xiaodong Zhu   +5 more
wiley   +1 more source

Machine learning-based unified models for predicting drug clearance from pharmacokinetic animal and study design variables. [PDF]

PLoS One
Ampadi Ramachandran R, Tell LA, Mercer MA, Xu X, Millagaha Gedara NI, Clapham MO, Lin Z, Riviere JE, Jaberi-Douraki M.   +8 more
europepmc   +1 more source