AIMC Topic: Prospective Studies
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Comparative analysis of kidney function prediction: traditional statistical methods vs. deep learning techniques.
Clinical and experimental nephrology
Jan 15, 2025
BACKGROUND: Chronic kidney disease (CKD) represents a significant public health challenge, with rates consistently on the rise. Enhancing kidney function prediction could contribute to the early detection, prevention, and management of CKD in clinica...
Clinical validation of explainable AI for fetal growth scans through multi-level, cross-institutional prospective end-user evaluation.
Scientific reports
Jan 15, 2025
We aimed to develop and evaluate Explainable Artificial Intelligence (XAI) for fetal ultrasound using actionable concepts as feedback to end-users, using a prospective cross-center, multi-level approach. We developed, implemented, and tested a deep-l...
Comparison of cardiovascular risk prediction models developed using machine learning based on data from a Sri Lankan cohort with World Health Organization risk charts for predicting cardiovascular risk among Sri Lankans: a cohort study.
BMJ open
Jan 15, 2025
INTRODUCTION: Models derived from non-Sri Lankan cohorts are used for cardiovascular (CV) risk stratification of Sri Lankans.
Golgi protein 73: charting new territories in diagnosing significant fibrosis in MASLD: a prospective cross-sectional study.
Frontiers in endocrinology
Jan 13, 2025
OBJECTIVES: To explore the correlation between serum Golgi protein 73 (GP73) levels and the degree of fibrosis in Metabolic dysfunction associated steatotic liver disease (MASLD); to establish a non-invasive diagnostic algorithm based on serum GP73 a...
Machine learning-based prediction model integrating ultrasound scores and clinical features for the progression to rheumatoid arthritis in patients with undifferentiated arthritis.
Clinical rheumatology
Jan 10, 2025
OBJECTIVES: Predicting rheumatoid arthritis (RA) progression in undifferentiated arthritis (UA) patients remains a challenge. Traditional approaches combining clinical assessments and ultrasonography (US) often lack accuracy due to the complex intera...
Machine learning techniques to predict diabetic ketoacidosis and HbA1c above 7% among individuals with type 1 diabetes - A large multi-centre study in Australia and New Zealand.
Nutrition, metabolism, and cardiovascular diseases : NMCD
Jan 9, 2025
BACKGROUND AND AIMS: Type 1 diabetes and diabetic ketoacidosis (DKA) have a significant impact on individuals and society across a wide spectrum. Our objective was to utilize machine learning techniques to predict DKA and HbA1c>7 %.
Glycated Hemoglobin
Risk Factors
New Zealand
Young Adult
Adult
Diabetic Ketoacidosis
Male
Decision Support Techniques
Support Vector Machine
Humans
Middle Aged
Prospective Studies
Australia
Machine Learning
Biomarkers
Predictive Value of Tests
Risk Assessment
Prognosis
Deep Learning
Female
Adolescent
Diabetes Mellitus, Type 1
Accelerated High-resolution T1- and T2-weighted Breast MRI with Deep Learning Super-resolution Reconstruction.
Academic radiology
Jan 9, 2025
RATIONALE AND OBJECTIVES: To assess the performance of an industry-developed deep learning (DL) algorithm to reconstruct low-resolution Cartesian T1-weighted dynamic contrast-enhanced (T1w) and T2-weighted turbo-spin-echo (T2w) sequences and compare ...
Machine learning algorithms for predicting delayed hyponatremia after transsphenoidal surgery for patients with pituitary adenoma.
Scientific reports
Jan 9, 2025
This study aimed to develop and validate machine learning (ML) models to predict the occurrence of delayed hyponatremia after transsphenoidal surgery for pituitary adenoma. We retrospectively collected clinical data on patients with pituitary adenoma...
Characterization of hepatocellular carcinoma with CT with deep learning reconstruction compared with iterative reconstruction and 3-Tesla MRI.
European radiology
Jan 8, 2025
OBJECTIVES: This study compared the characteristics of lesions suspicious for hepatocellular carcinoma (HCC) and their LI-RADS classifications in adaptive statistical iterative reconstruction (ASIR) and deep learning reconstruction (DLR) to those of ...
Assessment of Real-Time Natural Language Processing for Improving Diagnostic Specificity: A Prospective, Crossover Exploratory Study.
Applied clinical informatics
Jan 8, 2025
BACKGROUND: Reliable, precise, timely, and clear documentation of diagnoses is difficult. Poor specificity or the absence of diagnostic documentation can lead to decreased revenue and increased payor denials, audits, and queries to providers. Nuance...
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