Results 211 to 220 of about 24,864 (292)

Decoding temporal miRNA signatures of semen under in vitro exposure for forensic time since deposition estimation using machine learning‐driven modeling

Interdisciplinary Medicine, EarlyView.
This study develops a novel miRNA‐based framework for estimating the time since deposition of semen stains, combining small RNA sequencing with machine learning. Time‐dependent miRNA modules were identified using Mfuzz clustering and WGCNA, followed by a multi‐stage feature selection pipeline that reduced 261 candidate miRNAs to a minimal 7‐miRNA panel.
Meiming Cai, Qiong Lan, Tong Xie, Qinglin Liu, Ming Zhao, Xiaolian Wu, Xin Shi, Ruonan Shen, Yiman Wu, Chen Mao, Bin Cong, Bofeng Zhu   +11 more
wiley   +1 more source

Understanding Peelle's Pertinent Puzzle bias in generalized least squares regression through eigenspectrum analysis. [PDF]

Sci Rep
Walton NAW, Fritsch WN, Lewis AM, Forbes J, Neudecker D, Sobes V.   +5 more
europepmc   +1 more source

From Reactive to Proactive Volatility Modeling With Hemisphere Neural Networks

Journal of Applied Econometrics, EarlyView.
ABSTRACT We revisit maximum likelihood estimation (MLE) for macroeconomic density forecasting through a novel neural network architecture with dedicated mean and variance hemispheres. Our architecture features several key ingredients making MLE work in this context.
Philippe Goulet Coulombe, Mikael Frenette, Karin Klieber   +2 more
wiley   +1 more source

Regression approaches for modeling genotype-environment interaction and making predictions into unseen environments. [PDF]

Theor Appl Genet
Hrachov M, Piepho HP, Rahman NMF, Malik WA.   +3 more
europepmc   +1 more source

The mediating role of shame in the relationship between adolescent hairpulling and co‐occurring anxiety and depressive symptomology

JCPP Advances, EarlyView.
This study found that shame is a significant mediator in positive associations between hairpulling severity and depression and anxiety severity within a community sample of adolescents with clinical levels of hair‐pulling severity. It also found high levels of trance‐pulling and post‐pulling rituals.
Talia F. Mayerson, Clare Mackay, Polly Waite   +2 more
wiley   +1 more source

Prediction Modeling With Many Correlated and Zero-Inflated Predictors: Assessing the Nonnegative Garrote Approach. [PDF]

Stat Med
Gregorich M, Kammer M, Mischak H, Heinze G.   +3 more
europepmc   +1 more source

Deep Learning Integration in Optical Microscopy: Advancements and Applications

Microscopy Research and Technique, EarlyView.
It explores the integration of DL into optical microscopy, focusing on key applications including image classification, segmentation, and computational reconstruction. ABSTRACT Optical microscopy is a cornerstone imaging technique in biomedical research, enabling visualization of subcellular structures beyond the resolution limit of the human eye ...
Pottumarthy Venkata Lahari, Sagnika Dutta, H. Deeksha, Samreen A. Patel, Budheswar Dehury, Nirmal Mazumder   +5 more
wiley   +1 more source

Linear Dimensionality Reduction Methods for Analyzing Structured Biomedical Data: Existing Research and Future Opportunities. [PDF]

Wiley Interdiscip Rev Comput Stat
Wang Y.
europepmc   +1 more source

Derivation and validation of the Pediatric Community‐Acquired Pneumonia Severity (PedCAPS) score: A prospective cohort study

Journal of Hospital Medicine, EarlyView.
Abstract Introduction Community‐acquired pneumonia (CAP) is a frequent and costly cause of pediatric emergency department (ED) visits and hospitalizations. Previous prognostic tools for CAP are limited by small samples, single‐center or retrospective designs, lack of generalizability to ED settings, lack of biomarkers, or limited objective data.
Todd A. Florin, Ron Reeder, Lilliam Ambroggio, Richard M. Ruddy, Samir S. Shah, Allison Cator, Matthew J. Lipshaw, Geoffrey A. Capraro, Laura F. Sartori, Amy Y. Cheng, Leah Tzimenatos, Patrick S. Walsh, Claudia R. Morris, Chris A. Rees, Son H. McLaren, Tamar R. Lubell, Chari D. Larsen, Justin Moher, Eileen J. Klein, Shubhada Hooli, Nathan Kuppermann, Pediatric Emergency Care Applied Research Network (PECARN) PedCAPS Investigators   +21 more
wiley   +1 more source

Pitfalls in using ML to predict cognitive function performance. [PDF]

Sci Rep
Kuhles G, Hamdan S, Heim S, Eickhoff SB, Patil KR, Camilleri JA, Weis S.   +6 more
europepmc   +1 more source