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Deep learning in medical image analysis: A third eye for doctors.

Journal of stomatology, oral and maxillofacial surgery
AIM AND SCOPE: Artificial intelligence (AI) in medicine is a fast-growing field. The rise of deep learning algorithms, such as convolutional neural networks (CNNs), offers fascinating perspectives for the automation of medical image analysis. In this...

Shift in Potential Malaria Transmission Areas in India, Using the Fuzzy-Based Climate Suitability Malaria Transmission (FCSMT) Model under Changing Climatic Conditions.

International journal of environmental research and public health
The future implications of climate change on malaria transmission at the global level have already been reported, however such evidences are scarce and limited in India. Here our study aims to assess, identify and map the potential effects of climate...

Predicting likelihood of psychological disorders in PlayerUnknown's Battlegrounds (PUBG) players from Asian countries using supervised machine learning.

Addictive behaviors
Multiplayer Online Battle Arena (MOBA) has become one of the most popular genre of online video games played by gamers worldwide. Previous studies have exhibited that excessive engagement in games can lead to Internet Gaming Disorder (IGD). Internet ...

Machine learning analysis plans for randomised controlled trials: detecting treatment effect heterogeneity with strict control of type I error.

Trials
BACKGROUND: Retrospective exploratory analyses of randomised controlled trials (RCTs) seeking to identify treatment effect heterogeneity (TEH) are prone to bias and false positives. Yet the desire to learn all we can from exhaustive data measurements...

Development of a system based on artificial intelligence to identify visual problems in children: study protocol of the TrackAI project.

BMJ open
INTRODUCTION: Around 70% to 80% of the 19 million visually disabled children in the world are due to a preventable or curable disease, if detected early enough. Vision screening in childhood is an evidence-based and cost-effective way to detect visua...

Artificial Intelligence in Ophthalmology: Evolutions in Asia.

Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)
Artificial intelligence (AI) has been studied in ophthalmology since availability of digital information in ophthalmic care. The significant turning point was availability of commercial digital color fundus photography in the late 1990s, which caused...

Artificial intelligence for the detection of esophageal and esophagogastric junctional adenocarcinoma.

Journal of gastroenterology and hepatology
BACKGROUND AND AIM: Conventional endoscopy for the early detection of esophageal and esophagogastric junctional adenocarcinoma (E/J cancer) is limited because early lesions are asymptomatic, and the associated changes in the mucosa are subtle. There ...

Prediction of systemic biomarkers from retinal photographs: development and validation of deep-learning algorithms.

The Lancet. Digital health
BACKGROUND: The application of deep learning to retinal photographs has yielded promising results in predicting age, sex, blood pressure, and haematological parameters. However, the broader applicability of retinal photograph-based deep learning for ...