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Reproducibility of Results

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Leveraging deep transfer learning and explainable AI for accurate COVID-19 diagnosis: Insights from a multi-national chest CT scan study.

Computers in biology and medicine
The COVID-19 pandemic has emerged as a global health crisis, impacting millions worldwide. Although chest computed tomography (CT) scan images are pivotal in diagnosing COVID-19, their manual interpretation by radiologists is time-consuming and poten...

A fact based analysis of decision trees for improving reliability in cloud computing.

PloS one
The popularity of cloud computing (CC) has increased significantly in recent years due to its cost-effectiveness and simplified resource allocation. Owing to the exponential rise of cloud computing in the past decade, many corporations and businesses...

Assessing the efficacy of artificial intelligence to provide peri-operative information for patients with a stoma.

ANZ journal of surgery
BACKGROUND: Stomas present significant lifestyle and psychological challenges for patients, requiring comprehensive education and support. Current educational methods have limitations in offering relevant information to the patient, highlighting a po...

Reliability and quality of information provided by artificial intelligence chatbots on post-contrast acute kidney injury: an evaluation of diagnostic, preventive, and treatment guidance.

Revista da Associacao Medica Brasileira (1992)
OBJECTIVE: The aim of this study was to evaluate the reliability and quality of information provided by artificial intelligence chatbots regarding the diagnosis, preventive methods, and treatment of contrast-associated acute kidney injury, while also...

Validation of an Artificial Intelligence-based Tool - The Screening Corneal Objective Risk of Ectasia Integrated into Anterion for Detection of Corneal Ectasia/Risk of Ectasia.

Middle East African journal of ophthalmology
PURPOSE: The purpose of this study was to validate the artificial intelligence-based Screening Corneal Objective Risk of Ectasia (SCORE) for the detection of corneal ectasia/risk of ectasia and to find the mean SCORE value in normal eyes.

Utility of AI digital pathology as an aid for pathologists scoring fibrosis in MASH.

Journal of hepatology
BACKGROUND & AIMS: Intra and inter-pathologist variability poses a significant challenge in metabolic dysfunction-associated steatohepatitis (MASH) biopsy evaluation, leading to suboptimal selection of patients and confounded assessment of histologic...

Automatic classification of HEp-2 specimens by explainable deep learning and Jensen-Shannon reliability index.

Artificial intelligence in medicine
The Anti-Nuclear Antibodies (ANA) test using Human Epithelial type 2 (HEp-2) cells in the Indirect Immuno-Fluorescence (IIF) assay protocol is considered the gold standard for detecting Connective Tissue Diseases. Computer-assisted systems for HEp-2 ...

How reliable is artificial intelligence in the diagnosis of cholesteatoma on CT images?

American journal of otolaryngology
PURPOSE: This study analysed the main artificial intelligence (AI) models for the diagnosis of cholesteatoma on computed tomography (CT), evaluating their performance and comparing them with each other. The increasing application of AI in radiology r...

Keeping humans in the loop efficiently by generating question templates instead of questions using AI: Validity evidence on Hybrid AIG.

Medical teacher
BACKGROUND: Manually creating multiple-choice questions (MCQ) is inefficient. Automatic item generation (AIG) offers a scalable solution, with two main approaches: template-based and non-template-based (AI-driven). Template-based AIG ensures accuracy...