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Improved Automatic Grading of Diabetic Retinopathy Using Deep Learning and Principal Component Analysis.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Diabetic retinopathy (DR) is one of the most common chronic diseases around the world. Early screening and diagnosis of DR patients through retinal fundus is always preferred. However, image screening and diagnosis is a highly time-consuming task for...

Exploration of Machine Learning and Statistical Techniques in Development of a Low-Cost Screening Method Featuring the Global Diet Quality Score for Detecting Prediabetes in Rural India.

The Journal of nutrition
BACKGROUND: The prevalence of type 2 diabetes has increased substantially in India over the past 3 decades. Undiagnosed diabetes presents a public health challenge, especially in rural areas, where access to laboratory testing for diagnosis may not b...

Towards automatic diagnosis of rheumatic heart disease on echocardiographic exams through video-based deep learning.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Rheumatic heart disease (RHD) affects an estimated 39 million people worldwide and is the most common acquired heart disease in children and young adults. Echocardiograms are the gold standard for diagnosis of RHD, but there is a shortage ...

Electrocardiogram screening for aortic valve stenosis using artificial intelligence.

European heart journal
AIMS: Early detection of aortic stenosis (AS) is becoming increasingly important with a better outcome after aortic valve replacement in asymptomatic severe AS patients and a poor outcome in moderate AS. We aimed to develop artificial intelligence-en...

Application of Comprehensive Artificial intelligence Retinal Expert (CARE) system: a national real-world evidence study.

The Lancet. Digital health
BACKGROUND: Medical artificial intelligence (AI) has entered the clinical implementation phase, although real-world performance of deep-learning systems (DLSs) for screening fundus disease remains unsatisfactory. Our study aimed to train a clinically...

Creative Approaches for Assessing Long-term Outcomes in Children.

Pediatrics
Advances in new technologies, when incorporated into routine health screening, have tremendous promise to benefit children. The number of health screening tests, many of which have been developed with machine learning or genomics, has exploded. To as...

Applying Artificial Intelligence to Gynecologic Oncology: A Review.

Obstetrical & gynecological survey
IMPORTANCE: Artificial intelligence (AI) will play an increasing role in health care. In gynecologic oncology, it can advance tailored screening, precision surgery, and personalized targeted therapies.

Artificial Intelligence Algorithm for Screening Heart Failure with Reduced Ejection Fraction Using Electrocardiography.

ASAIO journal (American Society for Artificial Internal Organs : 1992)
Although heart failure with reduced ejection fraction (HFrEF) is a common clinical syndrome and can be modified by the administration of appropriate medical therapy, there is no adequate tool available to perform reliable, economical, early-stage scr...

Addressing Artificial Intelligence Bias in Retinal Diagnostics.

Translational vision science & technology
PURPOSE: This study evaluated generative methods to potentially mitigate artificial intelligence (AI) bias when diagnosing diabetic retinopathy (DR) resulting from training data imbalance or domain generalization, which occurs when deep learning syst...

Screening and identifying hepatobiliary diseases through deep learning using ocular images: a prospective, multicentre study.

The Lancet. Digital health
BACKGROUND: Ocular changes are traditionally associated with only a few hepatobiliary diseases. These changes are non-specific and have a low detection rate, limiting their potential use as clinically independent diagnostic features. Therefore, we ai...