Results 91 to 100 of about 6,285,017 (364)

Study of cardiovascular disease prediction model based on random forest in eastern China

Scientific Reports, 2020
Cardiovascular disease (CVD) is the leading cause of death worldwide and a major public health concern. CVD prediction is one of the most effective measures for CVD control.
Li Yang, Hai-bin Wu, Xiaoqing Jin, P. Zheng, Shiyun Hu, Xiao-Lin Xu, Wei Yu, Jing Yan   +7 more
semanticscholar   +1 more source

Copy Number Variants and Their Association With Intracerebral Hemorrhage Risk: A Case–Control Study

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Introduction Intracerebral Hemorrhage (ICH) is a leading cause of morbidity and mortality worldwide and lacks effective therapeutic interventions. Despite previous studies, the genetic underpinnings of ICH remain poorly understood. We sought to investigate the role of copy number variants (CNVs) in ICH pathophysiology to identify novel ...
Savvina Prapiadou, Carl D. Langefeld, Padmini Sekar, Mary Comeau, Timothy Howard, Tamara N. Kimball, Chen Bowang, Hyacinth I. Hyacinth, Jonathan Rosand, Christopher D. Anderson, Caspar Grond‐Ginsbach, Daniel Woo, Stacie L. Demel   +12 more
wiley   +1 more source

Seed classification with random forest models

Applications in Plant Sciences
Premise To improve forest conservation monitoring, we developed a protocol to automatically count and identify the seeds of plant species with minimal resource requirements, making the process more efficient and less dependent on human operators. Methods
Josephine Elena Reek, Janneke Hille Ris Lambers, Eléonore Perret, Alana R. O. Chin   +3 more
doaj   +1 more source

Spatially Adaptive Random Forests [PDF]

2013 IEEE 10th International Symposium on Biomedical Imaging, 2013
Medical imaging protocols produce large amounts of multi- modal volumetric images. The large size of the datasets contributes to the success of supervised discriminative methods for semantic image segmentation. Classifying relevant structures in medical images is challenging due to (a) the large size of data volumes, and (b) the severe class overlap in
Geremia, Ezequiel, Menze, Bjoern, Ayache, Nicholas   +2 more
openaire   +2 more sources

Basilar Artery Occlusion Stroke Managed With Tenecteplase Versus Alteplase Before Endovascular Treatment (BAO‐TNK)

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To compare the effectiveness and safety of tenecteplase (TNK) versus alteplase (TPA) in patients with basilar artery occlusion prior to endovascular treatment (EVT). Methods In this retrospective multicenter study (BAO‐TNK), we analyzed consecutive BAO patients from 14 U.S.
Rahul R. Karamchandani, Dylan N. Wolman, Tyler M. Bielinski, Nitin Goyal, Jeremy B. Rhoten, Mahesh V. Jayaraman, Christian T. Sidebottom, Bradley A. Gross, Alhamza R. Al‐Bayati, Mohamed F. Doheim, Matthew K. Tobin, Anoop Chinthala, Avi Gajjar, Justin Mascitelli, Matthew R. Webb, Jan‐Karl Burkhardt, Kyle W. Scott, Visish Srinivasan, Daniel Tonetti, Manisha Koneru, David J. Altschul, Dhrumhil Vaishnav, Sumeet Multani, Thana Theofanis, William J. Ares, Je Yeong Sone, Ramin Zand, Sasan Bahrami, Jiang Li, Gary Defilipp, Dale Strong, Radmehr Torabi, Krisztina Moldovan, Kelsey E. Kline, Clemens M. Schirmer, Raul G. Nogueira, Alexandra R. Paul, Bradley N. Bohnstedt, Philipp Hendrix   +38 more
wiley   +1 more source

A tale of two "forests": random forest machine learning AIDS tropical forest carbon mapping.

PLoS ONE, 2014
Accurate and spatially-explicit maps of tropical forest carbon stocks are needed to implement carbon offset mechanisms such as REDD+ (Reduced Deforestation and Degradation Plus).
Joseph Mascaro, Gregory P Asner, David E Knapp, Ty Kennedy-Bowdoin, Roberta E Martin, Christopher Anderson, Mark Higgins, K Dana Chadwick   +7 more
doaj   +1 more source

AI-based smart prediction of clinical disease using random forest classifier and Naive Bayes

Journal of Supercomputing, 2020
Healthcare practices include collecting all kinds of patient data which would help the doctor correctly diagnose the health condition of the patient.
V. Jackins, S. Vimal, M. Kaliappan, Mi Young Lee   +3 more
semanticscholar   +1 more source

Deep Learning–Assisted Differentiation of Four Peripheral Neuropathies Using Corneal Confocal Microscopy

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Peripheral neuropathies contribute to patient disability but may be diagnosed late or missed altogether due to late referral, limitation of current diagnostic methods and lack of specialized testing facilities. To address this clinical gap, we developed NeuropathAI, an interpretable deep learning–based multiclass classification ...
Chaima Ben Rabah, Ioannis N. Petropoulos, Mark Stettner, Maryam Ferdousi, Uazman Alam, Nathan Efron, Ahmed Serag, Rayaz A. Malik   +7 more
wiley   +1 more source

Banzhaf random forests: Cooperative game theory based random forests with consistency [PDF]

Neural Networks, 2018
Random forests algorithms have been widely used in many classification and regression applications. However, the theory of random forests lags far behind their applications. In this paper, we propose a novel random forests classification algorithm based on cooperative game theory.
Jianyuan Sun, Guoqiang Zhong, Kaizhu Huang, Junyu Dong   +3 more
openaire   +3 more sources

Age‐Related Characteristics of SYT1‐Associated Neurodevelopmental Disorder

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objectives We describe the clinical manifestations and developmental abilities of individuals with SYT1‐associated neurodevelopmental disorder (Baker‐Gordon syndrome) from infancy to adulthood. We further describe the neuroradiological and electrophysiological characteristics of the condition at different ages, and explore the associations ...
Sam G. Norwitz, Josefine Eck, Joel S. Winston, Kate Baker   +3 more
wiley   +1 more source