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An interpretable hybrid machine learning approach for predicting three-month unfavorable outcomes in patients with acute ischemic stroke.
International journal of medical informatics
Jan 22, 2025
BACKGROUND: Acute ischemic stroke (AIS) is a clinical disorder caused by nontraumatic cerebrovascular disease with a high incidence, mortality, and disability rate. Most stroke survivors are left with speech and physical impairments, and emotional pr...
Deep learning based prediction of depression and anxiety in patients with type 2 diabetes mellitus using regional electronic health records.
International journal of medical informatics
Jan 22, 2025
BACKGROUND: Depression and anxiety are prevalent mental health conditions among individuals with type 2 diabetes mellitus (T2DM), who exhibit unique vulnerabilities and etiologies. However, existing approaches fail to fully utilize regional heterogen...
Hip prosthesis failure prediction through radiological deep sequence learning.
International journal of medical informatics
Jan 22, 2025
BACKGROUND: Existing deep learning studies for the automated detection of hip prosthesis failure only consider the last available radiographic image. However, using longitudinal data is thought to improve the prediction, by combining temporal and spa...
Predicting Postoperative Infection After Cytoreductive Surgery and Hyperthermic Intraperitoneal Chemotherapy with Splenectomy.
Annals of surgical oncology
Jan 22, 2025
BACKGROUND: Hematologic changes after splenectomy and hyperthermic intraperitoneal chemotherapy (HIPEC) can complicate postoperative assessment of infection. This study aimed to develop a machine-learning model to predict postoperative infection afte...
Gait Video-Based Prediction of Severity of Cerebellar Ataxia Using Deep Neural Networks.
Movement disorders : official journal of the Movement Disorder Society
Jan 22, 2025
BACKGROUND: Pose estimation algorithms applied to two-dimensional videos evaluate gait disturbances; however, a few studies have used this method to evaluate ataxic gait.
Diagnostic Performance of Different Examination Types and Learning Curves of Radiologists for 5G-Based Robot-Assisted Tele-Ultrasonography: A Prospective and Large-Scale Study.
Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
Jan 22, 2025
OBJECTIVE: To investigate the feasibility of remotely providing routine ultrasound (US) examinations to patients using a fifth-generation-based robot-assisted tele-ultrasonography (RATU) system in a real-world setting.
A multimodal deep learning model for cervical pre-cancers and cancers prediction: Development and internal validation study.
Computers in biology and medicine
Jan 22, 2025
BACKGROUND: The current cervical cancer screening and diagnosis have limitations due to their subjectivity and lack of reproducibility. We describe the development of a deep learning (DL)-based diagnostic risk prediction model and evaluate its potent...
A prospective and comparative study on improving the diagnostic accuracy of early gastric cancer based on deep convolutional neural network real-time diagnosis system (with video).
Surgical endoscopy
Jan 22, 2025
BACKGROUND: Endoscopic diagnosis of early gastric cancer (EGC) is a challenge. It is not clear whether deep convolutional neural network (DCNN) model could improve the endoscopists' diagnostic performance.
Multimodal integration using a machine learning approach facilitates risk stratification in HR+/HER2- breast cancer.
Cell reports. Medicine
Jan 22, 2025
Hormone receptor-positive (HR+)/human epidermal growth factor receptor 2-negative (HER2-) breast cancer is the most common type of breast cancer, with continuous recurrence remaining an important clinical issue. Current relapse predictive models in H...
Functional Disability and Psychological Impact in Headache Patients: A Comparative Study Using Conventional Statistics and Machine Learning Analysis.
Medicina (Kaunas, Lithuania)
Jan 22, 2025
: Recent research has focused on exploring the relationships between various factors associated with headaches and understanding their impact on individuals' psychological states. Utilizing statistical methods and machine learning models, these studi...
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