Comparison of model feature importance statistics to identify covariates that contribute most to model accuracy in prediction of insomnia
AA Huang, SY Huang - Plos one, 2024 - journals.plos.org
Importance Sleep is critical to a person's physical and mental health and there is a need to
create high performing machine learning models and critically understand how models rank …
create high performing machine learning models and critically understand how models rank …
Machine Learning Applications in Acute Coronary Syndrome: Diagnosis, Outcomes and Management
S Nie, S Zhang, Y Zhao, X Li, H Xu, Y Wang… - Advances in …, 2024 - Springer
Acute coronary syndrome (ACS) is a leading cause of death worldwide. Prompt and
accurate diagnosis of acute myocardial infarction (AMI) or ACS is crucial for improved …
accurate diagnosis of acute myocardial infarction (AMI) or ACS is crucial for improved …
Dual-centre harmonised multimodal positron emission tomography/computed tomography image radiomic features and machine learning algorithms for non-small cell …
Aims We aimed to build radiomic models for classifying non-small cell lung cancer (NSCLC)
histopathological subtypes through a dual-centre dataset and comprehensively evaluate the …
histopathological subtypes through a dual-centre dataset and comprehensively evaluate the …
Left Ventricular Myocardial Dysfunction Evaluation in Thalassemia Patients Using Echocardiographic Radiomic Features and Machine Learning Algorithms
Heart failure caused by iron deposits in the myocardium is the primary cause of mortality in
beta-thalassemia major patients. Cardiac magnetic resonance imaging (CMRI) T2* is the …
beta-thalassemia major patients. Cardiac magnetic resonance imaging (CMRI) T2* is the …
Myocardial perfusion SPECT radiomic features reproducibility assessment: Impact of image reconstruction and harmonization
Background Coronary artery disease (CAD) has one of the highest mortality rates in humans
worldwide. Single‐photon emission computed tomography (SPECT) myocardial perfusion …
worldwide. Single‐photon emission computed tomography (SPECT) myocardial perfusion …
[PDF][PDF] 人工智能在心脏多模态影像中的应用
余妙如， 张德富， 曾伟， 盛媛媛， 罗舒榆… - 临床心血管病 …, 2023 - lcxxgen.whuhzzs.com
人工智能(artificialintelligence, AI) 在医疗领域的应用正在逐渐发展壮大. 通过多种模态影像数据
分析可以帮助医生提高诊断效率, 减少劳动强度, 以及打破医疗的时空限制等 …
分析可以帮助医生提高诊断效率, 减少劳动强度, 以及打破医疗的时空限制等 …
Comparison of Machine Learning Algorithms Using Manual/Automated Features on 12-Lead Signal Electrocardiogram Classification: A Large Cohort Study on …
Propose An electrocardiogram (ECG) has been extensively used to detect rhythm
disturbances. We sought to determine the accuracy of different machine learning in …
disturbances. We sought to determine the accuracy of different machine learning in …
[HTML][HTML] Fully Automated Region-Specific Human-Perceptive-Equivalent Image Quality Assessment: Application to 18F-FDG PET Scans
Results In the head and neck, chest, chest-abdomen interval, abdomen, and pelvis regions,
the best models achieved area under the curve, accuracy, sensitivity, and specificity of [0.97 …
the best models achieved area under the curve, accuracy, sensitivity, and specificity of [0.97 …
Prospective study of dual-phase 99mTc-MIBI SPECT/CT nomogram for differentiating non-small cell lung cancer from benign pulmonary lesions
L Cheng, H Gao, Z Wang, L Guo, X Wang… - European Journal of …, 2024 - Elsevier
Objectives To establish and validate a technetium 99m sestamibi (99m Tc-MIBI) single-
photon emission computed tomography/computed tomography (SPECT/CT) nomogram for …
photon emission computed tomography/computed tomography (SPECT/CT) nomogram for …
Advances in the application of artificial intelligence in multimodality cardiac imaging
YU Miaoru, Z Defu, Z Wei, S Yuanyuan… - J Clin …, 2023 - en.whuhzzs.com
Abstract The application of Artificial Intelligence (AI) in the medical field is gradually
developing. Multi-modal image data analysis can help doctors improve diagnostic efficiency …
developing. Multi-modal image data analysis can help doctors improve diagnostic efficiency …