AI Medical Compendium Topic

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Development and external validation of machine learning-based models to predict patients with cellulitis developing sepsis during hospitalisation.

BMJ open
OBJECTIVE: Cellulitis is the most common cause of skin-related hospitalisations, and the mortality of patients with sepsis remains high. Some stratification models have been developed, but their performance in external validation has been unsatisfact...

External validation of a 2-year all-cause mortality prediction tool developed using machine learning in patients with stage 4-5 chronic kidney disease.

Journal of nephrology
BACKGROUND: Chronic kidney disease (CKD) is associated with increased mortality. Individual mortality prediction could be of interest to improve individual clinical outcomes. Using an independent regional dataset, the aim of the present study was to ...

Discovery of urinary biosignatures for tuberculosis and nontuberculous mycobacteria classification using metabolomics and machine learning.

Scientific reports
Nontuberculous mycobacteria (NTM) infection diagnosis remains a challenge due to its overlapping clinical symptoms with tuberculosis (TB), leading to inappropriate treatment. Herein, we employed noninvasive metabolic phenotyping coupled with comprehe...

A deep learning-based algorithm for pulmonary tuberculosis detection in chest radiography.

Scientific reports
In tuberculosis (TB), chest radiography (CXR) patterns are highly variable, mimicking pneumonia and many other diseases. This study aims to evaluate the efficacy of Google teachable machine, a deep neural network-based image classification tool, to d...

Automated detection of type 1 ROP, type 2 ROP and A-ROP based on deep learning.

Eye (London, England)
PURPOSE: To provide automatic detection of Type 1 retinopathy of prematurity (ROP), Type 2 ROP, and A-ROP by deep learning-based analysis of fundus images obtained by clinical examination using convolutional neural networks.

A Combination of Machine Learning and PBPK Modeling Approach for Pharmacokinetics Prediction of Small Molecules in Humans.

Pharmaceutical research
PURPOSE: Recently, there has been rapid development in model-informed drug development, which has the potential to reduce animal experiments and accelerate drug discovery. Physiologically based pharmacokinetic (PBPK) and machine learning (ML) models ...

Artificial intelligence in hepatocellular carcinoma diagnosis: a comprehensive review of current literature.

Journal of gastroenterology and hepatology
BACKGROUND AND AIM: Hepatocellular carcinoma (HCC) diagnosis mainly relies on its pathognomonic radiological profile, obviating the need for biopsy. The project of incorporating artificial intelligence (AI) techniques in HCC aims to improve the perfo...

Multi-label classification of retinal diseases based on fundus images using Resnet and Transformer.

Medical & biological engineering & computing
Retinal disorders are a major cause of irreversible vision loss, which can be mitigated through accurate and early diagnosis. Conventionally, fundus images are used as the gold diagnosis standard in detecting retinal diseases. In recent years, more a...

Deep learning-based pathological prediction of lymph node metastasis for patient with renal cell carcinoma from primary whole slide images.

Journal of translational medicine
BACKGROUND: Metastasis renal cell carcinoma (RCC) patients have extremely high mortality rate. A predictive model for RCC micrometastasis based on pathomics could be beneficial for clinicians to make treatment decisions.

Enhancing the diagnosis of functionally relevant coronary artery disease with machine learning.

Nature communications
Functionally relevant coronary artery disease (fCAD) can result in premature death or nonfatal acute myocardial infarction. Its early detection is a fundamentally important task in medicine. Classical detection approaches suffer from limited diagnost...