AIMC Topic: Incidence

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Integrating Machine Learning and Traditional Survival Analysis to Identify Key Predictors of Foveal Involvement in Geographic Atrophy.

Investigative ophthalmology & visual science
PURPOSE: The purpose of this study was to investigate the incidence of foveal involvement in geographic atrophy (GA) secondary to age-related macular degeneration (AMD), using machine learning to assess the importance of risk factors.

Predicting malaria outbreaks using earth observation measurements and spatiotemporal deep learning modelling: a South Asian case study from 2000 to 2017.

The Lancet. Planetary health
BACKGROUND: Malaria remains one the leading communicable causes of death. Approximately half of the world's population is considered at risk of infection, predominantly in African and South Asian countries. Although malaria is preventable, heterogene...

[Effect of EIT-guided individualized PEEP setting on the incidence of hypoxemia in elderly patients undergoing robot-assisted radical prostatectomy].

Zhonghua yi xue za zhi
To investigate the effect of individualized positive end expiratory pressure (PEEP) setting guided by chest electrical impedance tomography (EIT) on the incidence of hypoxemia in elderly patients undergoing robot-assisted radical prostatectomy in th...

A Novel Early Warning Model for Hand, Foot and Mouth Disease Prediction Based on a Graph Convolutional Network.

Biomedical and environmental sciences : BES
OBJECTIVES: Hand, foot and mouth disease (HFMD) is a widespread infectious disease that causes a significant disease burden on society. To achieve early intervention and to prevent outbreaks of disease, we propose a novel warning model that can accur...

A deep-learning system predicts glaucoma incidence and progression using retinal photographs.

The Journal of clinical investigation
BackgroundDeep learning has been widely used for glaucoma diagnosis. However, there is no clinically validated algorithm for glaucoma incidence and progression prediction. This study aims to develop a clinically feasible deep-learning system for pred...

[Research progress of in-hospital mortality risk model in patients with acute myocardial infarction].

Zhonghua wei zhong bing ji jiu yi xue
The incidence of in-hospital death in acute myocardial infarction (AMI) is high, which seriously threatens the life and health of patients. At present, many countries and regions have established a variety of objective assessment models for predictin...

The relationship between rising temperatures and malaria incidence in Hainan, China, from 1984 to 2010: a longitudinal cohort study.

The Lancet. Planetary health
BACKGROUND: The influence of rising global temperatures on malaria dynamics and distribution remains controversial, especially in central highland regions. We aimed to address this subject by studying the spatiotemporal heterogeneity of malaria and t...

A Machine Learning Understanding of Sepsis.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Sepsis is a serious cause of morbidity and mortality and yet its pathophysiology remains elusive. Recently, medical and technological advances have helped redefine the criteria for sepsis incidence, which is otherwise poorly understood. With the reco...

Relationship of age, atherosclerosis and angiographic stenosis using artificial intelligence.

Open heart
OBJECTIVE: The study evaluates the relationship of coronary stenosis, atherosclerotic plaque characteristics (APCs) and age using artificial intelligence enabled quantitative coronary computed tomographic angiography (AI-QCT).