AIMC Topic: Reproducibility of Results

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An application of deep learning model InceptionTime to predict nausea, vomiting, diarrhoea, and constipation using the gastro-intestinal pacemaker activity drug database (GIPADD).

Scientific reports Apr 16, 2025
The accurate preclinical prediction of adverse drug reactions (ADRs), such as nausea and vomiting, remains a challenge. The Gastro-Intestinal Pacemaker Activity Drug Database (GIPADD) ( http://www.gutrhythm.com/public_database ) is a new source of el...
Humans Reproducibility of Results Deep Learning Big Data Diarrhea Vomiting Databases, Pharmaceutical Biological Clocks Electrodiagnosis Digestive System Diseases Predictive Learning Models ROC Curve Area Under Curve Feasibility Studies Drug-Related Side Effects and Adverse Reactions Gastrointestinal Tract Constipation Nausea
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Assessing the Quality and Reliability of ChatGPT's Responses to Radiotherapy-Related Patient Queries: Comparative Study With GPT-3.5 and GPT-4.

JMIR cancer Apr 16, 2025
BACKGROUND: Patients frequently resort to the internet to access information about cancer. However, these websites often lack content accuracy and readability. Recently, ChatGPT, an artificial intelligence-powered chatbot, has signified a potential p...
Radiotherapy Neoplasms Humans Surveys and Questionnaires Artificial Intelligence Generative Artificial Intelligence Reproducibility of Results Internet
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Accuracy, consistency, and contextual understanding of large language models in restorative dentistry and endodontics.

Journal of dentistry Apr 15, 2025
OBJECTIVE: This study aimed to evaluate and compare the performance of several large language models (LLMs) in the context of restorative dentistry and endodontics, focusing on their accuracy, consistency, and contextual understanding.
Dentistry, Operative Large Language Models Education, Dental Endodontics Comprehension Humans Reproducibility of Results
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Cuffless Blood Pressure Measurement: Where Do We Actually Stand?

Hypertension (Dallas, Tex. : 1979) Apr 15, 2025
Cuffless blood pressure (BP) measurement offers considerable potential for clinical practice but is a challenging technological field. Many are investigating pulse wave analysis with or without pulse arrival time in which machine learning is applied ...
Hypertension Blood Pressure Determination Blood Pressure Pulse Wave Analysis Humans Reproducibility of Results
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Multiple instance learning-based prediction of programmed death-ligand 1 (PD-L1) expression from hematoxylin and eosin (H&E)-stained histopathological images in breast cancer.

PeerJ Apr 15, 2025
Programmed death-ligand 1 (PD-L1) is an important biomarker increasingly used as a predictive marker in breast cancer immunotherapy. Immunohistochemical quantification remains the standard method for assessment. However, it presents challenges relate...
Eosine Yellowish-(YS) Hematoxylin Multiple-Instance Learning Algorithms Deep Learning Humans B7-H1 Antigen Reproducibility of Results Female Staining and Labeling Breast Neoplasms Immunohistochemistry Biomarkers, Tumor
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Uncertainty-aware segmentation quality prediction via deep learning Bayesian Modeling: Comprehensive evaluation and interpretation on skin cancer and liver segmentation.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Apr 13, 2025
Image segmentation is a critical step in computational biomedical image analysis, typically evaluated using metrics like the Dice coefficient during training and validation. However, in clinical settings without manual annotations, assessing segmenta...
Bayes Theorem Reproducibility of Results Image Interpretation, Computer-Assisted Humans Deep Learning Uncertainty Skin Neoplasms Liver Neoplasms Image Processing, Computer-Assisted
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HALSR-Net: Improving CNN Segmentation of Cardiac Left Ventricle MRI with Hybrid Attention and Latent Space Reconstruction.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Apr 12, 2025
Accurate cardiac MRI segmentation is vital for detailed cardiac analysis, yet the manual process is labor-intensive and prone to variability. Despite advancements in MRI technology, there remains a significant need for automated methods that can reli...
Humans Neural Networks, Computer Reproducibility of Results Image Processing, Computer-Assisted Heart Ventricles Image Interpretation, Computer-Assisted Magnetic Resonance Imaging, Cine
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External Validation of an Artificial Intelligence Algorithm Using Biparametric MRI and Its Simulated Integration with Conventional PI-RADS for Prostate Cancer Detection.

Academic radiology Apr 11, 2025
PURPOSE: Prostate imaging reporting and data systems (PI-RADS) experiences considerable variability in inter-reader performance. Artificial Intelligence (AI) algorithms were suggested to provide comparable performance to PI-RADS for assessing prostat...
Artificial Intelligence Algorithms Magnetic Resonance Imaging Retrospective Studies Aged Prostatic Neoplasms Humans Reproducibility of Results Sensitivity and Specificity Image Interpretation, Computer-Assisted Male Radiology Information Systems Middle Aged
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Prevalence of low-flow state by automated machine-learning 3D echocardiography in patients with moderate-to-severe aortic stenosis and normal ejection-fraction.

The international journal of cardiovascular imaging Apr 10, 2025
BACKGROUND: In aortic valve stenosis (AS), measurement of stroke volume index (SVi) by the 2D Doppler- technique is required to calculate the aortic valve area (AVA) and determine flow status but is prone to systematic errors.
Ventricular Function, Left Stroke Volume Prevalence Severity of Illness Index Aged Aged, 80 and over Male Image Interpretation, Computer-Assisted Automation Echocardiography, Doppler Blood Flow Velocity Hemodynamics Aortic Valve Stenosis Aortic Valve Predictive Value of Tests Humans Machine Learning Female Reproducibility of Results Echocardiography, Three-Dimensional
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Evaluating the agreement between ChatGPT-4 and validated questionnaires in screening for anxiety and depression in college students: a cross-sectional study.

BMC psychiatry Apr 10, 2025
BACKGROUND: The Chat Generative Pre-trained Transformer (ChatGPT), an artificial intelligence-based web application, has demonstrated substantial potential across various knowledge domains, particularly in medicine. This cross-sectional study assesse...
Anxiety Disorders Male Humans Reproducibility of Results Universities Psychiatric Status Rating Scales Female Young Adult Psychometrics Depression Mass Screening Adult Adolescent Surveys and Questionnaires Students Cross-Sectional Studies ROC Curve Anxiety Generative Artificial Intelligence
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