Results 251 to 260 of about 1,014,031 (308)

Semantically redundant training data removal and deep model classification performance: A study with chest X-rays. [PDF]

Comput Med Imaging Graph
Rajaraman S, Zamzmi G, Yang F, Liang Z, Xue Z, Antani S.   +5 more
europepmc   +1 more source

Location‐Specific Hematoma Volume Predicts Early Neurological Deterioration in Supratentorial ICH

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Early neurological deterioration (END) adversely affects outcomes in patients with intracerebral hemorrhage (ICH). This study aimed to determine the location‐specific hematoma volumes for END in supratentorial ICH patients. Methods We retrospectively analyzed supratentorial ICH patients presenting from two prospective cohorts.
Zuoqiao Li, Guilin Meng, Zijie Wang, Xiao Hu, Jing Cheng, Chu Chen, Tiannan Yang, Jiaxin Luo, Zizhen Meng, Xueyun Liu, Qi Li   +10 more
wiley   +1 more source

TopoGeoFusion: Integrating object topology based feature computation methods into geometrical feature analysis to enhance classification performance. [PDF]

MethodsX
Rani NS, Sai KS, Pushpa BR, Krishna AS, Sangamesha MA, Bhavya KR, Devadas RM, Hiremani V.   +7 more
europepmc   +1 more source

Classification performance bias between training and test sets in a limited mammography dataset. [PDF]

PLoS One
Hou R, Lo JY, Marks JR, Hwang ES, Grimm LJ.   +4 more
europepmc   +1 more source

Improved Classification Performance of Bacteria in Interference Using Raman and Fourier-Transform Infrared Spectroscopy Combined with Machine Learning. [PDF]

Molecules
Zhang P, Xu J, Du B, Yang Q, Liu B, Xu J, Tong Z.   +6 more
europepmc   +1 more source

Comparing human text classification performance and explainability with large language and machine learning models using eye-tracking. [PDF]

Sci Rep
Divya Venkatesh J, Jaiswal A, Nanda G.
europepmc   +1 more source

Mock community taxonomic classification performance of publicly available shotgun metagenomics pipelines. [PDF]

Sci Data
Valencia EM, Maki KA, Dootz JN, Barb JJ.
europepmc   +1 more source

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A classification performance measure considering the degree of classification difficulty

Neurocomputing, 2016
In the field of classification, classification difficulty of instances is one of vital factors that influence the performance of classifiers, however it has been totally neglected. In this paper, a new performance measure for classification algorithms based on Receiver Operator Characteristic (ROC) curves is proposed with the ability of incorporating ...
Xiaoli Zhang, Xiongfei Li, Yuncong Feng   +2 more
exaly   +2 more sources