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Efficient Neural Network Classification of Parkinson's Disease and Schizophrenia Using Resting-State EEG Data.
Brain topography
Feb 17, 2025
Timely identification of Parkinson's disease and schizophrenia is crucial for the effective management and enhancement of patients' quality of life. The utilization of electroencephalogram (EEG) monitoring applications has proven instrumental in diag...
Multimodal machine learning-based model for differentiating nontuberculous mycobacteria from .
Frontiers in public health
Feb 17, 2025
OBJECTIVE: To develop and evaluate the effectiveness of multimodal machine learning approach for the differentiation of NTM from MTB.
Diagnosis of Benign and Malignant Newly Developed Nodules on the Surgical Side After Breast Cancer Surgery Based on Machine Learning.
The breast journal
Feb 17, 2025
To enhance the diagnostic accuracy of new nodules on the surgical side after breast cancer surgery using machine learning techniques and to explore the role of multifeature fusion. Data from 137 breast cancer postoperative patients with new nodules...
Machine learning model based on preoperative contrast-enhanced CT and clinical features to predict perineural invasion in gallbladder carcinoma patients.
European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
Feb 16, 2025
BACKGROUND: Perineural invasion (PNI) is an independent prognostic risk factor for gallbladder carcinoma (GBC). However, there is currently no reliable method for the preoperative noninvasive prediction of PNI.
Cultural variation in trust and acceptability of artificial intelligence diagnostics for dementia.
Journal of Alzheimer's disease : JAD
Feb 16, 2025
Digital health innovations hold diagnostic and therapeutic promise but may be subject to biases for underrepresented groups. We explored perceptions of using artificial intelligence (AI) diagnostics for dementia through a focus group as part of the A...
Development and clinical evaluation of an AI-assisted respiratory state classification system for chest X-rays: A BMI-Specific approach.
Computers in biology and medicine
Feb 16, 2025
PURPOSE: In this study, we aimed to develop and clinically evaluate an artificial intelligence (AI)-assisted support system for determining inhalation and exhalation states on chest X-ray images, focusing on the specific challenge of respiratory stat...
Development and validation of MRI-derived deep learning score for non-invasive prediction of PD-L1 expression and prognostic stratification in head and neck squamous cell carcinoma.
Cancer imaging : the official publication of the International Cancer Imaging Society
Feb 16, 2025
BACKGROUND: Immunotherapy has revolutionized the treatment landscape for head and neck squamous cell carcinoma (HNSCC) and PD-L1 combined positivity score (CPS) scoring is recommended as a biomarker for immunotherapy. Therefore, this study aimed to d...
Predicting visual field global and local parameters from OCT measurements using explainable machine learning.
Scientific reports
Feb 16, 2025
Glaucoma is characterised by progressive vision loss due to retinal ganglion cell deterioration, leading to gradual visual field (VF) impairment. The standard VF test may be impractical in some cases, where optical coherence tomography (OCT) can offe...
Hybrid multi-modality multi-task learning for forecasting progression trajectories in subjective cognitive decline.
Neural networks : the official journal of the International Neural Network Society
Feb 15, 2025
While numerous studies strive to exploit the complementary potential of MRI and PET using learning-based methods, the effective fusion of the two modalities remains a tricky problem due to their inherently distinctive properties. In addition, current...
CT-Based Deep Learning Predicts Prognosis in Esophageal Squamous Cell Cancer Patients Receiving Immunotherapy Combined with Chemotherapy.
Academic radiology
Feb 15, 2025
RATIONALE AND OBJECTIVES: Immunotherapy combined with chemotherapy has improved outcomes for some esophageal squamous cell carcinoma (ESCC) patients, but accurate pre-treatment risk stratification remains a critical gap. This study constructed a deep...
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