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Mass Screening

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Deep forest model for diagnosing COVID-19 from routine blood tests.

Scientific reports
The Coronavirus Disease 2019 (COVID-19) global pandemic has threatened the lives of people worldwide and posed considerable challenges. Early and accurate screening of infected people is vital for combating the disease. To help with the limited quant...

Using deep learning to assist readers during the arbitration process: a lesion-based retrospective evaluation of breast cancer screening performance.

European radiology
OBJECTIVES: To evaluate if artificial intelligence (AI) can discriminate recalled benign from recalled malignant mammographic screening abnormalities to improve screening performance.

Diagnostic performance of deep-learning-based screening methods for diabetic retinopathy in primary care-A meta-analysis.

PloS one
BACKGROUND: Diabetic retinopathy (DR) affects 10-24% of patients with diabetes mellitus type 1 or 2 in the primary care (PC) sector. As early detection is crucial for treatment, deep learning screening methods in PC setting could potentially aid in a...

Deep learning methods for screening patients' S-ICD implantation eligibility.

Artificial intelligence in medicine
Subcutaneous Implantable Cardioverter-Defibrillators (S-ICDs) are used for prevention of sudden cardiac death triggered by ventricular arrhythmias. T Wave Over Sensing (TWOS) is an inherent risk with S-ICDs which can lead to inappropriate shocks. A m...

Detection of subclinical rheumatic heart disease in children using a deep learning algorithm on digital stethoscope: a study protocol.

BMJ open
INTRODUCTION: Rheumatic heart diseases (RHDs) contribute significant morbidity and mortality globally. To reduce the burden of RHD, timely initiation of secondary prophylaxis is important. The objectives of this study are to determine the frequency o...

Real-world artificial intelligence-based opportunistic screening for diabetic retinopathy in endocrinology and indigenous healthcare settings in Australia.

Scientific reports
This study investigated the diagnostic performance, feasibility, and end-user experiences of an artificial intelligence (AI)-assisted diabetic retinopathy (DR) screening model in real-world Australian healthcare settings. The study consisted of two c...

Five regions, five retinopathy screening programmes: a systematic review of how Portugal addresses the challenge.

BMC health services research
BACKGROUND: The implementation of a population-based screening programme for diabetic retinopathy involves several challenges, often leading to postponements and setbacks at high human and material costs. Thus, it is of the utmost importance to promo...

Artificial Intelligence-Enabled Electrocardiography to Screen Patients with Dilated Cardiomyopathy.

The American journal of cardiology
Undiagnosed dilated cardiomyopathy (DC) can be asymptomatic or present as sudden cardiac death, therefore pre-emptively identifying and treating patients may be beneficial. Screening for DC with echocardiography is expensive and labor intensive and s...

Effect of a deep learning-based system on the miss rate of gastric neoplasms during upper gastrointestinal endoscopy: a single-centre, tandem, randomised controlled trial.

The lancet. Gastroenterology & hepatology
BACKGROUND: White light endoscopy is a pivotal first-line tool for the detection of gastric neoplasms. However, gastric neoplasms can be missed during upper gastrointestinal endoscopy due to the subtle nature of these lesions and varying skill among ...