Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 60,881 to 60,890 of 228,300 articles

Large-scale proteomics profiling of peripheral blood of DM1 patients identifies biomarkers for disease severity and functional capacity.

Journal of neuromuscular diseases
BackgroundMyotonic Dystrophy Type 1 (DM1), the most common genetic neuromuscular disorder in adults, poses significant challenges for drug development due to its multisystem nature and high clinical variability in symptoms and disease progression. Wi... read more 

G.AI.A: An Integrated Machine-Learning Platform for Predicting Bioaccumulation and Ecotoxicity of Pharmaceuticals.

Journal of chemical information and modeling
Pharmaceutical pollution in aquatic environments poses a significant ecological threat due to the accumulation of bioactive compounds from human and veterinary sources. In support of the EU Green Deal's Chemicals Strategy for Sustainability, this stu... read more 

How to Evaluate the Accuracy of Symptom Checkers and Diagnostic Decision Support Systems: Symptom Checker Accuracy Reporting Framework (SCARF).

JMIR human factors
Symptom checkers are apps and websites that assist medical laypeople in diagnosing their symptoms and determining which course of action to take. When evaluating these tools, previous studies primarily used an approach introduced a decade ago that la... read more 

Using Latent Dirichlet Allocation Topic Modeling to Uncover Latent Research Topics and Trends in Renal Cell Carcinoma: Bibliometric Review.

JMIR cancer
BACKGROUND: Renal cell carcinoma (RCC) is a common, often lethal kidney cancer that originates in the renal cortex. Its incidence is rising, and major factors include smoking, obesity, and hypertension, though its etiology is uncertain. While surgery... read more 

Treatment Recommendations for Clinical Deterioration on the Wards: Development and Validation of Machine Learning Models.

JMIR AI
BACKGROUND: Clinical deterioration in general ward patients is associated with increased morbidity and mortality. Early and appropriate treatments can improve outcomes for such patients. While machine learning (ML) tools have proven successful in the... read more 

Development of Venous Thromboembolism Risk Prediction Models Based on Whole Blood Gene Expression Profiling Using 20 Machine Learning Algorithms: Comprehensive Analysis Study.

JMIR medical informatics
BACKGROUND: There is a lack of venous thromboembolism (VTE) risk prediction models based on gene expression information. OBJECTIVE: This study aimed to construct a VTE prediction model based on whole blood gene expression profiling, by performing a c... read more 

Learning the anatomical topology consistency driven by Wasserstein distance for weakly supervised 3D pancreas registration in multi-phase CT images.

Biomedical physics & engineering express
Accurate and automatic registration of the pancreas between contrast-enhanced CT (CECT) and non-contrast CT (NCCT) images is crucial for diagnosing and treating pancreatic cancer. However, existing deep learning-based methods remain limited due to in... read more 

Magnetic resonance imaging-based proton dose calculation for pelvic tumors using deep learning.

Physics in medicine and biology
Objective Magnetic resonance imaging (MRI)-only proton therapy combines high soft tissue contrast with high-precision dose distributions. However, conventional dose calculation is impossible on MRI due to missing electron density information. Thi... read more 

Institution-specific pre-treatment quality assurance control and specification limits: a tool to implement a new formalism and criteria optimization using statistical process control and heuristic methods.

Physics in medicine and biology
OBJECTIVE: Establishing control and specification limits for Volumetric Modulated Arc Therapy (VMAT) pre-treatment quality assurance (PTQA) is essential for streamlining PTQA workflows and optimizing plan complexity. This study aimed to develop and i... read more 

Unlocking the potential of nailfold videocapillaroscopy in diagnosing and staging wild-type transthyretin amyloidosis: A preliminary approach.

Medicina clinica
BACKGROUND: Wild-type transthyretin amyloidosis (ATTRwt) is a serious condition. At early stages, symptoms resemble those of heart failure with preserved ejection fraction (HFpEF). Our aim was to perform software-supported nailfold videocapillaroscop... read more