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A machine learning-based prediction model for sepsis-associated delirium in intensive care unit patients with sepsis-associated acute kidney injury.
Renal failure
Jun 2, 2025
Sepsis-associated acute kidney injury (SA-AKI) patients in the ICU often suffer from sepsis-associated delirium (SAD), which is linked to unfavorable outcomes. This research aimed to develop a machine learning-based model for early SAD prediction in ...
Detecting and Remediating Harmful Data Shifts for the Responsible Deployment of Clinical AI Models.
JAMA network open
Jun 2, 2025
IMPORTANCE: Clinical artificial intelligence (AI) systems are susceptible to performance degradation due to data shifts, which can lead to erroneous predictions and potential patient harm. Proactively detecting and mitigating these shifts is crucial ...
Accuracy of Artificial Intelligence for Gatekeeping in Referrals to Specialized Care.
JAMA network open
Jun 2, 2025
IMPORTANCE: Integrating artificial intelligence (AI) technologies into gatekeeping holds significant potential, as it efficiently handles repetitive tasks and can process large amounts of information quickly.
Unsupervised learning-based quantitative analysis of CT intratumoral subregions predicts risk stratification of bladder cancer patients.
BMC medicine
Jun 2, 2025
BACKGROUND: Preoperative diagnosis of muscle invasion and American Joint Committee on Cancer (AJCC) stage plays a crucial role in guiding treatment strategies for bladder cancer (BCa). Utilizing quantitative analysis of tumor subregions via CT imagin...
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 ...
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...
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.
Utility of artificial intelligence-based conversation voice analysis for detecting cognitive decline.
PloS one
Jun 2, 2025
Recent developments in artificial intelligence (AI) have introduced new technologies that can aid in detecting cognitive decline. This study developed a voice-based AI model that screens for cognitive decline using only a short conversational voice s...
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