AIMC Topic: Adult

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Quality Assessment of Large Language Model-Generated Medical Dialogue for Clinical Vignettes: Evaluation Study.

JMIR formative research
BACKGROUND: Traditional clinical vignettes, though widely used in medical education, often focus on prototypical presentations; require substantial time and effort to develop; and fail to represent patient diversity, the complexity of clinical condit...

Evaluating the Clinical Effectiveness and Patient Experience of a Large Language Model-Based Digital Tool for Home-Based Blood Pressure Management: Mixed Methods Study.

JMIR mHealth and uHealth
BACKGROUND: Hypertension, one of the most common cardiovascular conditions worldwide, necessitates comprehensive management due to its association with multiple health risks. Effective control often involves lifestyle changes and continuous monitorin...

MRI-Based Quantification of Intratumoral Heterogeneity for Predicting Progression-Free Survival in Patients with Lung Cancer Brain Metastasis Receiving Radiotherapy.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Our aim was to investigate the potential of using MRI-based habitat features for predicting progression-free survival (PFS) in patients with lung cancer brain metastasis (LCBM) receiving radiotherapy.

Machine learning models for predicting renal injury in patients with gout.

Renal failure
BACKGROUND: Renal injury is a severe complication among individuals diagnosed with gout. This research constructed a machine learning predictive model to assess renal injury risk in gout patients.

From conventional scores to explainable AI: a six-method comparative framework for failure prediction in percutaneous nephrolithotomy.

World journal of urology
OBJECTIVE: Percutaneous nephrolithotomy is the gold standard for treating large kidney stones. However, traditional scoring systems and logistic regression-based models have limited predictive power due to their reliance on linear assumptions. This s...

Machine learning-assisted aroma profile prediction in tomato puree based on flavoromics.

Food chemistry
Flavor serves as a key quality indicator in tomato puree (TP) processing; however, conventional methods often fall short in providing rapid and accurate assessments. To address this limitation, this study integrated flavoromics with machine learning ...

Exploring multidrug resistance patterns in community-acquired urinary tract infections with machine learning.

Antimicrobial agents and chemotherapy
While associations of antibiotic resistance traits are not random in multidrug-resistant (MDR) bacteria, clinically relevant resistance patterns remain underexplored. This study used association-set mining to explore resistance associations within i...

Machine learning to predict the role of CHWs in shifting birth preferences away from homebirth in India.

Scientific reports
This study utilized well-known supervised machine learning algorithms to NFHS‑5 data of West Bengal, India, to predict the place of birth (home vs facility) by integrating CHW (community health worker) contact factors and women participant's percepti...

Deep learning for motion classification in ankle exoskeletons using surface EMG and IMU signals.

Scientific reports
Ankle exoskeletons have garnered considerable interest for their potential to enhance mobility, support rehabilitation, and reduce fall risks, particularly among the aging population. Their effectiveness depends on accurate, real-time prediction of u...

Artificial intelligence improves detection and classification of pulmonary venous hypertension related to left ventricular diastolic dysfunction by chest radiography.

Scientific reports
Isolated-Left Ventricular Diastolic Dysfunction [LVDD] ranges (and may progress) from preclinical asymptomatic, symptomatic-LVDD, to LVDD-predominate Heart Failure [HF] presentations; if recognized early, LVDD progression might be preventable. Curren...