AIMC Topic: Artificial Intelligence

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Exploring optimal control of epidemic spread using reinforcement learning.

Scientific reports
Pandemic defines the global outbreak of a disease having a high transmission rate. The impact of a pandemic situation can be lessened by restricting the movement of the mass. However, one of its concomitant circumstances is an economic crisis. In thi...

Prediction of disease progression in patients with COVID-19 by artificial intelligence assisted lesion quantification.

Scientific reports
To investigate the value of artificial intelligence (AI) assisted quantification on initial chest CT for prediction of disease progression and clinical outcome in patients with coronavirus disease 2019 (COVID-19). Patients with confirmed COVID-19 inf...

Artificial Intelligence in Coronary Computed Tomography Angiography: From Anatomy to Prognosis.

BioMed research international
Cardiac computed tomography angiography (CCTA) is widely used as a diagnostic tool for evaluation of coronary artery disease (CAD). Despite the excellent capability to rule-out CAD, CCTA may overestimate the degree of stenosis; furthermore, CCTA anal...

Development of a Self-Harm Monitoring System for Victoria.

International journal of environmental research and public health
The prevention of suicide and suicide-related behaviour are key policy priorities in Australia and internationally. The World Health Organization has recommended that member states develop self-harm surveillance systems as part of their suicide preve...

Artificial Intelligence in the Fight Against COVID-19: Scoping Review.

Journal of medical Internet research
BACKGROUND: In December 2019, COVID-19 broke out in Wuhan, China, leading to national and international disruptions in health care, business, education, transportation, and nearly every aspect of our daily lives. Artificial intelligence (AI) has been...

The Emerging Hazard of AI-Related Health Care Discrimination.

The Hastings Center report
Artificial intelligence holds great promise for improved health-care outcomes. But it also poses substantial new hazards, including algorithmic discrimination. For example, an algorithm used to identify candidates for beneficial "high risk care manag...

A Distributed Black-Box Adversarial Attack Based on Multi-Group Particle Swarm Optimization.

Sensors (Basel, Switzerland)
Adversarial attack techniques in deep learning have been studied extensively due to its stealthiness to human eyes and potentially dangerous consequences when applied to real-life applications. However, current attack methods in black-box settings ma...

HDEC: A Heterogeneous Dynamic Ensemble Classifier for Binary Datasets.

Computational intelligence and neuroscience
In recent years, ensemble classification methods have been widely investigated in both industry and literature in the field of machine learning and artificial intelligence. The main advantage of this approach is to benefit from a set of classifiers i...

Development of a deep learning-based image eligibility verification system for detecting and filtering out ineligible fundus images: A multicentre study.

International journal of medical informatics
BACKGROUND: Recent advances in artificial intelligence (AI) have shown great promise in detecting some diseases based on medical images. Most studies developed AI diagnostic systems only using eligible images. However, in real-world settings, ineligi...