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Facial expression analysis using convolutional neural network for drug-naive and chronic schizophrenia.
Journal of psychiatric research
Nov 29, 2024
OBJECTIVE: Facial images have been shown to convey mental conditions as clinical symptoms. This study aimed to use facial images to detect patients with drug-naive schizophrenia (DN-SCZ) or chronic schizophrenia (C-SCZ) from healthy controls (HCs), a...
Fair and explainable Myocardial Infarction (MI) prediction: Novel strategies for feature selection and class imbalance correction.
Computers in biology and medicine
Nov 29, 2024
The rising incidences of myocardial infarction (MI), often affecting individuals without traditional risk factors, highlight the urgent need for improved early detection using personal health data. However, health surveys and electronic health record...
Combining MRI radiomics and clinical features for early identification of drug-resistant epilepsy in people with newly diagnosed epilepsy.
Epilepsy & behavior : E&B
Nov 29, 2024
OBJECTIVE: To identify newly diagnosed patients with drug-resistant epilepsy (DRE) based on radiomics and clinical features.
Integrating Interpretability in Machine Learning and Deep Neural Networks: A Novel Approach to Feature Importance and Outlier Detection in COVID-19 Symptomatology and Vaccine Efficacy.
Viruses
Nov 29, 2024
In this study, we introduce a novel approach that integrates interpretability techniques from both traditional machine learning (ML) and deep neural networks (DNN) to quantify feature importance using global and local interpretation methods. Our meth...
Prediction model for ocular metastasis of breast cancer: machine learning model development and interpretation study.
BMC cancer
Nov 29, 2024
BACKGROUND: Breast cancer (BC) is caused by the uncontrolled proliferation of breast epithelial cells followed by malignant transformation, and it has the highest incidence among female malignant tumors. The metastasis of BC occurs through direct and...
Predicting the time to get back to work using statistical models and machine learning approaches.
BMC medical research methodology
Nov 29, 2024
BACKGROUND: Whether machine learning approaches are superior to classical statistical models for survival analyses, especially in the case of lack of proportionality, is unknown.
Prognostic prediction for HER2-low breast cancer patients using a novel machine learning model.
BMC cancer
Nov 29, 2024
BACKGROUNDS: To develop a machine learning (ML) model for predicting the prognosis of breast cancer (BC) patients with low human epidermal growth factor receptor 2 (HER2) expression, and to investigate the association between clinicopathological char...
Developing a prediction model for cognitive impairment in older adults following critical illness.
BMC geriatrics
Nov 29, 2024
BACKGROUND: New or worsening cognitive impairment or dementia is common in older adults following an episode of critical illness, and screening post-discharge is recommended for those at increased risk. There is a need for prediction models of post-I...
Machine learning based on alcohol drinking-gut microbiota-liver axis in predicting the occurrence of early-stage hepatocellular carcinoma.
BMC cancer
Nov 29, 2024
BACKGROUND: Alcohol drinking and gut microbiota are related to hepatocellular carcinoma (HCC), but the specific relationship between them remains unclear.
Predicting early mortality in hemodialysis patients: a deep learning approach using a nationwide prospective cohort in South Korea.
Scientific reports
Nov 29, 2024
Early mortality after hemodialysis (HD) initiation significantly impacts the longevity of HD patients. This study aimed to quantify the effect sizes of risk factors on mortality using various machine learning approaches. A cohort of 3284 HD patients ...
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