Results 81 to 90 of about 4,433,966 (292)

Variable Importance Matching for Causal Inference

, 2023
Our goal is to produce methods for observational causal inference that are auditable, easy to troubleshoot, accurate for treatment effect estimation, and scalable to high-dimensional data. We describe a general framework called Model-to-Match that achieves these goals by (i) learning a distance metric via outcome modeling, (ii) creating matched groups ...
Quinn Lanners, Harsh Parikh, Alexander Volfovsky, Cynthia Rudin, David Page   +4 more
openaire   +3 more sources

Inpatient Food Insecurity and Pediatric Hematology Oncology Hospitalization Outcomes

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Children with cancer and blood disorders are at risk for food insecurity (FI). We aimed to describe the association of inpatient food insecurity (IFI) and hospitalization outcomes among patients admitted to the pediatric hematology oncology service. Of 325 caregivers screened for IFI, 60 (18.6%) screened positive.
Joanna M. Robles, Greg Russell, Leila H. DeWitt, Kimberly Montez, Callie L. Brown   +4 more
wiley   +1 more source

Predicting Pre-planting Risk of Stagonospora nodorum blotch in Winter Wheat Using Machine Learning Models

Frontiers in Plant Science, 2016
Pre-planting factors have been associated with the late-season severity of Stagonospora nodorum blotch (SNB), caused by the fungal pathogen Parastagonospora nodorum, in winter wheat (Triticum aestivum).
Lucky eMehra, Christina eCowger, Kevin eGross, Peter eOjiambo   +3 more
doaj   +1 more source

A Global Short Rotation Coppice (SRC) Willow Dataset for the Bioeconomy: Implications for the Yield in the United Kingdom

GCB Bioenergy
Short rotation coppice (SRC) willow is a second‐generation lignocellulosic energy crop with a background of research and breeding programmes carried out globally for more than three decades.
Antonio Castellano Albors, Anita Shepherd, Ian Shield, William Macalpine, Kevin Lindegaard, Ian Tubby, Astley Hastings   +6 more
doaj   +1 more source

Developing an Optimal Spatial Predictive Model for Seabed Sand Content Using Machine Learning, Geostatistics, and Their Hybrid Methods

Geosciences, 2019
Seabed sediment predictions at regional and national scales in Australia are mainly based on bathymetry-related variables due to the lack of backscatter-derived data. In this study, we applied random forests (RFs), hybrid methods of RF and geostatistics,
Jin Li, Justy Siwabessy, Zhi Huang, Scott Nichol   +3 more
doaj   +1 more source

Variable Importance Without Impossible Data

Annual Review of Statistics and Its Application
The most popular methods for measuring importance of the variables in a black-box prediction algorithm make use of synthetic inputs that combine predictor variables from multiple observations. These inputs can be unlikely, physically impossible, or even logically impossible.
Masayoshi Mase, Art B. Owen, Benjamin B. Seiler   +2 more
openaire   +2 more sources

Health‐Related Quality of Life and Symptom Severity Among Patients With PIK3CA‐Related Overgrowth Spectrum: A Mixed‐Methods Study to Understand Real‐World Experience With Alpelisib Treatment

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background PIK3CA‐related overgrowth spectrum (PROS) includes several rare overgrowth disorders resulting from somatic gain‐of‐function mutations in PIK3CA. Despite treatment advances, including the recent approval of alpelisib for PROS in the United States, literature detailing the patient experience with PROS is limited.
Vamsi Bollu, Kaitlin LaGasse, Cory D. Saucier, Kimberly Raymond, Miranda Lauher‐Charest, Lauren Crowder, Beilei Cai, Mary Lisha Paul, Denise Adams   +8 more
wiley   +1 more source

Modelling the Importance of Ground and Strong‐Motion Variables on the Damage Status in the 2023 Kahramanmaraş Earthquakes Using Supervised Machine Learning

Geoscience Data Journal
The damage status of 44 locations was investigated, incorporating ground condition parameters such as Vs30, engineering bedrock depth (EBd), and predominant frequency (f0), as well as strong‐motion parameters including PGA, Repi, and Rrup (epicentre and ...
Mustafa Senkaya, Serhat E. Akhanlı, Ali Silahtar, Hasan Karaaslan   +3 more
doaj   +1 more source

Fuzzy Forests: Extending Random Forest Feature Selection for Correlated, High-Dimensional Data

Journal of Statistical Software, 2019
In this paper we introduce fuzzy forests, a novel machine learning algorithm for ranking the importance of features in high-dimensional classification and regression problems. Fuzzy forests is specifically designed to provide relatively unbiased rankings
Daniel Conn, Tuck Ngun, Gang Li, Christina M. Ramirez   +3 more
doaj   +1 more source

‘They Need to Hear You Say It’: Healthcare Professionals’ Perspectives on Barriers and Enablers to End‐of‐Life Discussions With Adolescents and Young Adults With Cancer

Pediatric Blood &Cancer, EarlyView.
ABSTRACT End‐of‐life conversations with adolescents and young adults (AYAs) with cancer rarely occur without the guidance of healthcare professionals. As a part of the ‘Difficult Discussions’ study, focused on palliative care and advance care planning discussions with AYAs with cancer, we investigated the factors that healthcare professionals identify ...
Justine Lee, Holly Evans, Claire E. Wakefield, Antoinette Anazodo, Richard J. Cohn, Brittany C. McGill, Elizabeth A. Lobb, Lori Wiener, Madeleine L. Juhrmann, Ursula M. Sansom‐Daly   +9 more
wiley   +1 more source