AIMC Topic: Health Resources

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AI-Assisted Cardiovascular Risk Assessment by General Practitioners in Resource-Constrained Indonesian Settings Using a Conceptual Prototype: Randomized Controlled Study.

Journal of medical Internet research
BACKGROUND: Preventive strategies integrated with digital health and artificial intelligence (AI) have significant potential to mitigate the global burden of atherosclerotic cardiovascular disease (ASCVD). AI-enabled clinical decision support (CDS) s...

Real-world data landscape for glaucoma in Europe: a questionnaire-based analysis of resources among European Glaucoma Society members.

BMJ open ophthalmology
BACKGROUND/AIMS: To investigate the landscape to support Europe-wide collaborative real-world data (RWD) collection, exploring whether required resources are available to glaucoma clinicians.

Transposing intensive care innovation from modern warfare to other resource-limited settings.

European journal of trauma and emergency surgery : official publication of the European Trauma Society
BACKGROUND: Delivering intensive care in conflict zones and other resource-limited settings presents unique clinical, logistical, and ethical challenges. These contexts, characterized by disrupted infrastructure, limited personnel, and prolonged fiel...

Neural networks to model COVID-19 dynamics and allocate healthcare resources.

Scientific reports
This study presents a neural network-based framework for COVID-19 transmission prediction and healthcare resource optimization. The model achieves high prediction accuracy by integrating epidemiological, mobility, vaccination, and environmental data ...

Bridging the Digital Divide: A Practical Roadmap for Deploying Medical Artificial Intelligence Technologies in Low-Resource Settings.

Population health management
In recent decades, the integration of artificial intelligence (AI) into health care has revolutionized diagnostics, treatment customization, and delivery. In low-resource settings, AI offers significant potential to address health care disparities ex...

Transforming Healthcare in Low-Resource Settings With Artificial Intelligence: Recent Developments and Outcomes.

Public health nursing (Boston, Mass.)
BACKGROUND: Artificial intelligence now encompasses technologies like machine learning, natural language processing, and robotics, allowing machines to undertake complex tasks traditionally done by humans. AI's application in healthcare has led to ad...

Portable ultrasound devices for obstetric care in resource-constrained environments: mapping the landscape.

Gates open research
BACKGROUND: The WHO's recommendations on antenatal care underscore the need for ultrasound assessment during pregnancy. Given that maternal and perinatal mortality remains unacceptably high in underserved regions, these guidelines are imperative for ...

Spatiotemporal sentiment variation analysis of geotagged COVID-19 tweets from India using a hybrid deep learning model.

Scientific reports
India is a hotspot of the COVID-19 crisis. During the first wave, several lockdowns (L) and gradual unlock (UL) phases were implemented by the government of India (GOI) to curb the virus spread. These phases witnessed many challenges and various day-...

Analysis of Clinical Parameters, Drug Consumption and Use of Health Resources in a Southern European Population with Alcohol Abuse Disorder during COVID-19 Pandemic.

International journal of environmental research and public health
The disruption in healthcare attention to people with alcohol dependence, along with psychological decompensation as a consequence of lockdown derived from the COVID-19 pandemic could have a negative impact on people who suffer from alcohol abuse dis...

Predicting Risks of Machine Translations of Public Health Resources by Developing Interpretable Machine Learning Classifiers.

International journal of environmental research and public health
We aimed to develop machine learning classifiers as a risk-prevention mechanism to help medical professionals with little or no knowledge of the patient's languages in order to predict the likelihood of clinically significant mistakes or incomprehens...