Results 201 to 210 of about 361,318 (294)

Improved genetic algorithm based on greedy and simulated annealing ideas for vascular robot ordering strategy. [PDF]

PLoS One
Wang Z, Huang Y, Zhang Y, Sheng Y, Lai X, Lu P.   +5 more
europepmc   +1 more source

Long‐term use of low‐dose aspirin for cancer prevention: A 20‐year longitudinal cohort study of 1,506,525 Hong Kong residents

International Journal of Cancer, EarlyView.
What's New? Low‐dose aspirin use over an extended period is associated with a reduced risk of colorectal cancer (CRC) and potentially other malignancies. Duration of use to derive such benefits, however, remains unclear. This retrospective study examined low‐dose aspirin use for possible chemoprotective effects among individuals in Hong Kong.
Amy Lam, Ziyu Hao, Karen Yiu, Stephen Chan, Francis Chan, Joseph Sung, Kelvin Tsoi   +6 more
wiley   +1 more source

A Learning Model with Memory in the Financial Markets

International Journal of Finance &Economics, EarlyView.
ABSTRACT Learning is central to a financial agent's aspiration to gain persistent strategic advantage in asset value maximisation. The implicit mechanism that transforms this aspiration into an observed value gain is the speed of error corrections (demonstrating, an agent's speed of learning) whilst facing increased uncertainty.
Shikta Singh, Supun Chandrasena, Yue Shi, Abdullah Alhussaini, Claude Diebolt, Martin Enilov, Tapas Mishra   +6 more
wiley   +1 more source

PNL: a software to build polygenic risk scores using a super learner approach based on PairNet, a Convolutional Neural Network. [PDF]

Bioinformatics
Chen TH, Lee CJ, Chen SP, Wu SJ, Fann CSJ.   +4 more
europepmc   +1 more source

Novel machine‐learning bioinformatics reveal distinct metabolic alterations for enhanced colorectal cancer diagnosis and monitoring

iMetaOmics, EarlyView.
The PANDA pipeline for colorectal cancer (CRC) analysis integrates metabolomic data from LC‐MS with machine learning techniques to classify CRC stages and predict biomarkers. Initially, the raw metabolomic data is processed using partial least squares discriminant analysis (PLS‐DA) to reduce dimensionality and highlight key features.
Rui Xu, Hyein Jung, Fouad Choueiry, Shiqi Zhang, Rachel Pearlman, Heather Hampel, Ning Jin, Jieli Li, Jiangjiang Zhu   +8 more
wiley   +1 more source

Advances in Cardiac Imaging and Genetic Testing for Diagnosis and Risk Stratification in Cardiomyopathies: 2024 Update. [PDF]

J Clin Med
Gasior T.
europepmc   +1 more source

Ensemble and consensus approaches to prediction of recessive inheritance for missense variants in human disease. [PDF]

Cell Rep Methods
Petrazzini BO, Balick DJ, Forrest IS, Cho J, Rocheleau G, Jordan DM, Do R.   +6 more
europepmc   +1 more source

A panoramic view of cotton resistance to Verticillium dahliae: From genetic architectures to precision genomic selection

iMeta, EarlyView.
This study identified 10 reliable quantitative trait loci (QTLs) governing cotton resistance to V. dahliae in various environments through a genome‐wide association analysis (GWAS) using an upland cotton population. The pyramid of these 10 elite alleles reduced the disease index of cotton to V. dahliae from 70 to 20.
Xiaojun Zhang, Shiming Liu, Peng Wu, Wanying Xu, Dingyi Yang, Yuqing Ming, Shenghua Xiao, Weiran Wang, Jun Ma, Xinhui Nie, Zhan Gao, Junyuan Lv, Fei Wu, Zhaoguang Yang, Baoxin Zheng, Ping Du, Jiangmei Wang, Hao Ding, Jie Kong, Alifu Aierxi, Yu Yu, Wei Gao, Zhongxu Lin, Chunyuan You, Keith Lindsey, Nataša Štajner, Maojun Wang, Jiahe Wu, Shuangxia Jin, Xianlong Zhang, Longfu Zhu   +30 more
wiley   +1 more source

Identifying individuals with rare disease variants by inferring shared ancestral haplotypes from SNP array data. [PDF]

NAR Genom Bioinform
Robertson E, Grinton BE, Oliver KL, Fearnley LG, Hildebrand MS, Sadleir LG, Scheffer IE, Berkovic SF, Bennett MF, Bahlo M.   +9 more
europepmc   +1 more source

Synthetic biology for medical biomaterials

Interdisciplinary Medicine, EarlyView.
Synthetic biology platform has been utilized to produce a variety of medical biomaterials (MBMs), such as polylactic acid (PLA), polyhydroxyalkanoates (PHAs), hyaluronic acid (HA), collagen (COL), poly(β‐malic acid) (PMLA), poly‐γ‐glutamic acid (γ‐PGA), alginate (ALG), chitosan (CS), bacterial cellulose (BC), and antimicrobial peptides (AMPs).
Tao Xu, Xiao‐Yun Huang, Jin‐Wei Dao, Da Xiao, Dai‐Xu Wei   +4 more
wiley   +1 more source