Latest AI and machine learning research in surveillance for healthcare professionals.
BACKGROUND: Unlike Papanicolaou tests, there are no commercially available computer-assisted automated screening systems for urine specimens. Despite The Paris System for Reporting Urinary Cytology, there still is poor interobserver agreement with urine cytology and many cases in which a definitive diagnosis cannot be made. In the current study, the authors have reported on the development of an i...
Diabetes is a global public health disease projected to affect 642 million adults by 2040, with about 75% residing in low- and middle-income countries. Diabetic retinopathy (DR) affects 1 in 3 people with diabetes and remains the leading cause of blindness in working-aged adults. There are 3 broad strategic imperatives to prevent blindness caused by DR. Primary prevention requires preventing or de...
With this review, we aimed to provide a synopsis of recently proposed applications of machine learning (ML) in radiology focusing on prostate magnetic...
Interventional pharmacology is one of medicine's most potent weapons against disease. These drugs, however, can result in damaging side effects and mu...
BACKGROUND: Falls among older adults are both a common reason for presentation to the emergency department, and a major source of morbidity and mortal...
The early and accurately detection of brucellosis incidence change is of great importance for implementing brucellosis prevention strategic health pla...
BackgroundManagement of thyroid nodules may be inconsistent between different observers and time consuming for radiologists. An artificial intelligenc...
BACKGROUND: Mortality surveillance is of fundamental importance to public health surveillance. The real-time recording of death certificates, thanks t...
Background Coronary CT angiography contains prognostic information but the best method to extract these data remains unknown. Purpose To use machine l...
OBJECTIVE: Virtual reality simulators track all movements and forces of simulated instruments, generating enormous datasets which can be further analy...
BACKGROUND: The use of linked data in the Semantic Web is a promising approach to add value to nutrition research. An ontology, which defines the logi...
BACKGROUND: The vigilant observation of medical devices during post-market surveillance (PMS) for identifying safety-relevant incidents is a non-trivi...
Background Risk stratification systems for thyroid nodules are often complicated and affected by low specificity. Continual improvement of these syste...
The way we categorise and classify cancer types dictates not only the way we diagnose and treat patients but also many of our decisions on biomarker a...
BACKGROUND: Worldwide, syndromic surveillance is increasingly used for improved and timely situational awareness and early identification of public he...
INTRODUCTION: Poor road and communication infrastructure pose major challenges to tuberculosis (TB) control in many regions of the world. TB surveilla...
In this paper, we give an overview of methodological issues related to the use of statistical learning approaches when analyzing high-dimensional gene...
This study focuses on identifying environmental health risk factors related to acute respiratory diseases using deep learning method. Based on respira...
Syndromic surveillance detects and monitors individual and population health indicators through sources such as emergency department records. Automate...
Comprehensive reviews of syndromic surveillance in animal health have highlighted the hindrances to integration and interoperability among systems whe...