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Using machine learning to identify Parkinson's disease severity subtypes with multimodal data.
Journal of neuroengineering and rehabilitation
Jun 2, 2025
BACKGROUND: Classifying and predicting Parkinson's disease (PD) is challenging because of its diverse subtypes based on severity levels. Currently, identifying objective biomarkers associated with disease severity that can distinguish PD subtypes in ...
Assessing medical students' readiness for artificial intelligence after pre-clinical training.
BMC medical education
Jun 2, 2025
BACKGROUND: Artificial intelligence (AI) is becoming increasingly relevant in healthcare, necessitating healthcare professionals' proficiency in its use. Medical students and practitioners require fundamental understanding and skills development to m...
Machine-learning model for predicting left atrial thrombus in patients with paroxysmal atrial fibrillation.
BMC cardiovascular disorders
Jun 2, 2025
OBJECTIVE: Left atrial thrombus (LAT) poses a significant risk for stroke and other thromboembolic complication in patients with atrial fibrillation (AF). This study aimed to evaluate the incidence and predictors of LAT in patients with paroxysmal AF...
Development of a neural network-based risk prediction model for mild cognitive impairment in older adults with functional disability.
BMC public health
Jun 2, 2025
BACKGROUND: Mild Cognitive Impairment (MCI) is a critical transitional stage between normal aging and Alzheimer's disease, and its early identification is essential for delaying disease progression.
Data-driven diabetes mellitus prediction and management: a comparative evaluation of decision tree classifier and artificial neural network models along with statistical analysis.
Scientific reports
Jun 2, 2025
Diabetes Mellitus is a chronic metabolic disorder affecting a substantial global population leading to complications such as retinopathy, nephropathy, neuropathy, foot problems, heart attacks, and strokes if left unchecked. Prompt detection and diagn...
Out-of-distribution reject option method for dataset shift problem in early disease onset prediction.
Scientific reports
Jun 2, 2025
Machine learning is increasingly used to predict lifestyle-related disease onset using health and medical data. However, its predictive accuracy for use is often hindered by dataset shift, which refers to discrepancies in data distribution between th...
Enhancing Antidiabetic Drug Selection Using Transformers: Machine-Learning Model Development.
JMIR medical informatics
Jun 2, 2025
BACKGROUND: Diabetes affects millions worldwide. Primary care physicians provide a significant portion of care, and they often struggle with selecting appropriate medications.
Closing the AI generalisation gap by adjusting for dermatology condition distribution differences across clinical settings.
EBioMedicine
Jun 2, 2025
BACKGROUND: Generalisation of artificial intelligence (AI) models to a new setting is challenging. In this study, we seek to understand the robustness of a dermatology (AI) model and whether it generalises from telemedicine cases to a new setting inc...
A Deep Learning-Based Artificial Intelligence Model Assisting Thyroid Nodule Diagnosis and Management: Pilot Results for Evaluating Thyroid Malignancy in Pediatric Cohorts.
Thyroid : official journal of the American Thyroid Association
Jun 2, 2025
Artificial intelligence (AI) models have shown promise in predicting malignant thyroid nodules in adults; however, research on deep learning (DL) for pediatric cases is limited. We evaluated the applicability of a DL-based model for assessing thyroi...
Application research of artificial intelligence software in the analysis of thyroid nodule ultrasound image characteristics.
PloS one
Jun 2, 2025
Thyroid nodule, as a common clinical endocrine disease, has become increasingly prevalent worldwide. Ultrasound, as the premier method of thyroid imaging, plays an important role in accurately diagnosing and managing thyroid nodules. However, there i...
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